Multimodal transport logistics center site selection method, device and equipment

Abstract

The invention provides a multimodal transport logistics center site selection method, device and equipment. The multimodal transport logistics center site selection method comprises the following steps: acquiring a plurality of multimodal transport logistics center site selection schemes; determining an actual value of each index in a preset site selection evaluation index system corresponding to each site selection scheme; a first-level single-sorting weight vector and a plurality of second-level single-sorting weight vectors are determined, the first-level single-sorting weight vector is a level single-sorting weight vector of the criterion layer relative to the target layer, and the second-level single-sorting weight vector is a level single-sorting weight vector of all indexes corresponding to any criterion relative to the criterion; according to the actual value of the index corresponding to each site selection scheme, the first-level single-ranking weight vector and each second-level single-ranking weight vector, a target site selection scheme is determined from the multiple site selection schemes, and the method can efficiently and accurately select a more reasonable multimodal transport logistics center layout address.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a method, device and equipment for site selection of a multimodal transport logistics center. Background Art

[0002] The multimodal logistics center is a key node for connecting and transshipping different modes of transport in the multimodal transport system. The high-level planning and construction of the multimodal logistics center is of great significance to enhancing the radiation and driving capacity of transportation hubs, improving the efficiency of the comprehensive transportation network, and continuously reducing transportation costs.

[0003] In the field of logistics center site selection and evaluation, domestic and foreign scholars have conducted a lot of research, and the relevant research focuses on the following aspects: (1) It is believed that the site selection of regional logistics centers should be adapted to the transportation hub network as much as possible, and take into account economic rationality, the distribution of service objects, and the conditions of auxiliary facilities such as water, electricity, and the Internet. On this basis, a hierarchical model for the site selection of regional logistics centers is established; (2) It is believed that the site selection of logistics parks should follow the principles of economic rationality, environmental rationality, use of existing warehousing facilities, gradual progress, coordination with regional and urban master plans, and structural rationality. The site selection factors are summarized into natural environment factors, business environment factors, infrastructure factors and other factors, and on this basis, a site selection evaluation index system is established; (3) The logistics park site selection evaluation index system is divided into three parts: social benefits, economic benefits and technical benefits. Specific indicators include functional completeness, functional reliability, multimodal transport coordination, distance from traffic arteries, and proximity to freight hubs; (4) Based on the fuzzy evaluation method, the non-cost factors in the site selection process are comprehensively considered to evaluate the site selection plan; (5) The evaluation method combining fuzzy Delphi method, hierarchical analysis method and grey correlation analysis is used to analyze and evaluate the site selection problem of the logistics park.

[0004] However, the existing evaluation methods and evaluation index systems for logistics center site selection are mostly aimed at ordinary logistics centers and are not suitable for the site selection of multimodal logistics centers that include multiple modes of transportation. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a method, device and equipment for selecting a location for a multimodal transport logistics center. Specifically, it includes:

[0006] In a first aspect, the present invention provides a method for selecting a location for a multimodal transport logistics center, comprising:

[0007] Obtain multiple multimodal logistics center site selection options;

[0008] Determine the actual value of each indicator in the preset site selection evaluation indicator system corresponding to each site selection scheme. The preset site selection evaluation indicator system includes a target layer, a criterion layer and an indicator layer from top to bottom. The target layer includes one target, the layer includes N criteria, and the indicator layer includes m indicators, where N and m are positive integers greater than 0, and m≥N;

[0009] Determine a first-level single-ranking weight vector and multiple second-level single-ranking weight vectors, wherein the first-level single-ranking weight vector is a hierarchical single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is a hierarchical single-ranking weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs;

[0010] A target site selection scheme is determined from a plurality of site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vector and each second-level single-ranking weight vector.

[0011] In a second aspect, the present invention further provides a multimodal transport logistics center site selection device, comprising:

[0012] An acquisition module, used to acquire multiple multimodal logistics center site selection plans;

[0013] A processing module is used to determine the actual value of each indicator in the preset site selection evaluation indicator system corresponding to each site selection scheme. The preset site selection evaluation indicator system includes a target layer, a criterion layer and an indicator layer from top to bottom. The target layer includes one target, the layer includes N criteria, and the indicator layer includes m indicators, wherein N and m are positive integers greater than 0, and m≥N;

[0014] The processing module is further used to determine a first-level single-ranking weight vector and a plurality of second-level single-ranking weight vectors, wherein the first-level single-ranking weight vector is a hierarchical single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is a hierarchical single-ranking weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs;

[0015] The processing module is also used to determine a target site selection scheme from multiple site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vector and each second-level single-ranking weight vector.

[0016] In a third aspect, the present invention further provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0017] Memory, used to store computer programs;

[0018] The processor is used to implement any method provided in the first aspect when executing a program stored in the memory.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, any one of the methods provided in the first aspect is implemented.

[0020] In a fifth aspect, the present invention provides a program product, which includes computer program instructions, and when the computer program instructions are executed, they can implement any of the methods provided in the first aspect.

[0021] Beneficial effects of the present invention:

[0022] The method, device and equipment for selecting a site for an intermodal logistics center provided by the present invention obtain multiple site selection schemes for an intermodal logistics center; determine the actual values ​​of various indicators in a preset site selection evaluation index system corresponding to each site selection scheme, wherein the preset site selection evaluation index system includes a target layer, a criterion layer and an indicator layer in order from top to bottom, wherein the target layer includes a target, the criterion layer includes N criteria, and the indicator layer includes m indicators, wherein N and m are positive integers greater than 0, and m≥N; determine a first-level single-ranking weight vector and multiple second-level single-ranking weight vectors, wherein the first-level single-ranking weight vector is a hierarchical single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is a hierarchical single-ranking weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs; determine a target site selection scheme from multiple site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vector and each second-level single-ranking weight vector, and a more reasonable multimodal logistics center layout address can be selected efficiently and accurately.

[0023] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of a process flow of a multimodal transport logistics center site selection method provided by the present invention;

[0025] Figure 2 A schematic diagram of the architecture of a site selection evaluation index system provided by the present invention;

[0026] Figure 3 A schematic diagram of an ascending semi-trapezoidal membership function image provided by the present invention;

[0027] Figure 4 A schematic structural diagram of a multimodal transport logistics center site selection device provided by the present invention. DETAILED DESCRIPTION

[0028] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0029] Figure 1 A schematic diagram of a multimodal transport logistics center site selection method provided by the present invention is shown in FIG. Figure 1 As shown, the method includes:

[0030] S101. Obtain multiple multimodal transport logistics center site selection plans.

[0031] Specifically, obtaining multiple site selection plans for multimodal logistics centers can be by directly obtaining specific site selection information predetermined by the user; or it can be based on the functional positioning of the multimodal logistics center, and comprehensively considering the regional natural conditions, industrial foundation, transportation conditions, and existing logistics facilities, and determining multiple site selection plans for the multimodal logistics center through corresponding calculations.

[0032] Optionally, the location selection principles for multimodal logistics centers include:

[0033] (1) The site selection should comply with the requirements of the regional economic and social development plan, including the district or city master plan, industrial layout plan, comprehensive transportation plan, etc.; (2) The site selection should fully consider market demand and be as close as possible to industrial parks, factories, mines, ports and other cargo distribution centers to facilitate cargo distribution; (3) The site selection should be close to existing terminal facilities to facilitate seamless connection of various modes of transportation; (4) The site selection should have the conditions for the layout of transportation routes to ensure smooth entry and exit of goods in the logistics center without interfering with the main transportation routes; (5) The transport capacity of different transportation modes connected to the site should be compatible with each other , to avoid congestion after operation; (6) The site should be surrounded by sufficient distribution transportation lines to facilitate the rapid distribution of goods; (7) The site should have good topographic, geological, hydrological, meteorological and construction conditions; (8) The site should meet environmental protection requirements; (9) The site should be located in an area with abundant labor resources and reasonable costs; (10) When selecting a site, land prices and availability, as well as future expansion possibilities should be considered; (11) Multimodal logistics centers should give priority to surrounding areas with mature industrial development to obtain good infrastructure supporting conditions and logistics market atmosphere.

[0034] S102: Determine the actual value of each indicator in the preset site selection evaluation indicator system corresponding to each site selection scheme.

[0035] Among them, the preset site selection evaluation index system includes a target layer, a criterion layer and an indicator layer from top to bottom, the target layer includes a target, the criterion layer includes N criteria, and the indicator layer includes M indicators, wherein N and M are positive integers greater than 0, and M≥N.

[0036] Figure 2A schematic diagram of the architecture of a site selection evaluation index system provided by the present invention, such as Figure 2 As shown, the goal is to select the location of a multimodal logistics center. In one possible implementation method, the criteria include planning rationality criteria, intermodal matching criteria, distribution convenience criteria, industrial coordination criteria, and environmental adaptability criteria.

[0037] The planning rationality criterion is used to reflect the adaptability of the location of the multimodal logistics center to the superior planning, logistics facilities, and land supply in the area where the location is located. The indicators corresponding to the planning rationality criterion include the conformity to the superior planning, the utilization of existing facilities, and the scalability of land.

[0038] The conformity of the higher-level planning is an indicator to measure the degree of conformity between the site selection of the multimodal logistics center and the higher-level planning of the area where the site selection is located. Specifically, it is an indicator to measure the degree of conformity between the project site selection and the higher-level planning of the region, land use, industrial development, transportation, etc. This indicator is suitable for qualitative evaluation. For example, it can be quantified by expert scoring method. The higher the conformity, the greater the score.

[0039] The utilization of existing facilities is an indicator to measure the difficulty of connecting the multimodal logistics center with existing logistics facilities. Specifically, it is an indicator to measure the difficulty of connecting the project with existing logistics facilities (ports, stations, transportation networks, etc.). This indicator is suitable for qualitative evaluation. For example, it can be quantified by expert scoring. The higher the utilization, the greater the score.

[0040] Land scalability is an indicator to measure the scalability of the spatial scale of a multimodal logistics center. This indicator is suitable for qualitative evaluation. For example, it can be quantified using an expert scoring method. The better the scalability, the greater the score.

[0041] The intermodal matching criterion is used to reflect the coordination and matching degree of different modes of transportation in terms of stations, routes and transport capacity based on the location selection of multimodal logistics centers. The indicators corresponding to the intermodal matching criterion include the rationality of the setting of connecting stations, the coordination of transportation route layout and the adaptability of transportation route capacity.

[0042] The rationality of the connection site setting is an indicator to measure whether the existing stations and ports that the multimodal logistics center relies on are conducive to the connection and conversion of different modes of transportation. Specifically, it can be examined from four aspects, namely whether the conditions for the layout of dedicated lines are met, whether the vehicle entry and exit are smooth, whether the vehicle assembly and marshaling are convenient, and whether the vehicle entry and exit will interfere with the main line operation. This indicator is suitable for qualitative evaluation. For example, it can be quantified using the expert scoring method. The better the rationality, the greater the score.

[0043] The coordination of transportation route layout is an indicator to measure the coordination of transportation route layout around the location of the multimodal logistics center. Specifically, it can be quantified by the connection rate of medium and high-level transportation routes between the logistics center and the surrounding major cargo distribution points. The larger the index value, the better the coordination of transportation route layout.

[0044] In a possible implementation, for any site selection scheme, determining the value of the coordination of the transportation route layout includes the following steps A1-A3:

[0045] A1. Obtain the total number of cargo distribution points that the multimodal transport logistics center intends to serve and the location of each cargo distribution point corresponding to the site selection plan.

[0046] A2. According to the location of the multimodal logistics center and the location of each cargo distribution point corresponding to the site selection plan, determine the number of target cargo distribution points corresponding to the site selection plan.

[0047] Among them, the target cargo distribution point is the cargo distribution point whose transportation route with the multimodal logistics center meets the preset conditions among all cargo distribution points corresponding to the site selection plan.

[0048] Exemplarily, the transportation routes between the target cargo distribution point and the multimodal logistics center are medium and high-level transportation routes such as level three and above roads and level four and above air routes.

[0049] A3. According to the total number of cargo distribution points corresponding to the site selection plan and the number of target cargo distribution points, the value of the coordination of the transportation route layout corresponding to the site selection plan is determined, which is expressed as:

[0050]

[0051] Among them, A 22 It represents the value of coordination of transportation route layout, e represents the number of target cargo distribution points, and L represents the total number of cargo distribution points that the multimodal logistics center intends to serve.

[0052] The adaptability of transport capacity is an indicator to measure the adaptability of the transport capacity of each mode of transport around the location of the multimodal logistics center and the future freight volume. Specifically, it can be quantified by the ratio of the future average daily freight volume to the transport capacity of each mode of transport. The smaller the index value, the better the adaptability of the transport capacity of the transport line.

[0053] In a possible implementation, for any site selection scheme, determining the value of the transport capacity adaptability of the transport line includes the following steps B1 and B2:

[0054] B1. Obtain the total number of transport modes involved in the multimodal logistics center corresponding to the site selection plan, the line transport capacity of each transport mode around the multimodal logistics center, and the predicted freight volume of each transport mode.

[0055] B2. Determine the value of the transport capacity adaptability of the transport line corresponding to the site selection plan based on the total number of transport modes involved in the multimodal logistics center corresponding to the site selection plan, the line transport capacity of each transport mode around the multimodal logistics center, and the predicted freight volume of each transport mode.

[0056] For example, the transport capacity adaptability value of the transport route corresponding to the site selection scheme can be determined according to the total number of transport modes involved in the multimodal transport logistics center corresponding to the site selection scheme, the daily transport capacity of each transport mode route around the multimodal transport logistics center, and the annual predicted freight volume of each transport mode, which is specifically expressed as:

[0057]

[0058] Among them, A 23 represents the value of the transport capacity adaptability of the transport route, k represents the index of the transport mode involved in the multimodal transport logistics center, k = 1, 2, 3, ..., K, K represents the total number of transport modes involved in the multimodal transport logistics center, D k represents the annual forecast freight volume of the kth mode of transportation, C k Represents the daily transport capacity of the k-th transport mode line.

[0059] The distribution convenience criterion is used to reflect the convenience of external transportation in the location of multimodal logistics centers. The corresponding indicators of the distribution convenience criterion include proximity to cargo distribution points, support for trunk transportation routes and the average technical level of connecting roads.

[0060] The proximity to the cargo distribution point is an indicator to measure the distance between the location of the multimodal logistics center and the cargo distribution point. Specifically, it can be quantitatively expressed by the average distance. The smaller the value of this indicator, the closer the location is to the cargo distribution center.

[0061] In a possible implementation, for any site selection scheme, determining the value of proximity to a cargo distribution point includes the following steps C1 and C2:

[0062] C1. Obtain the total number of cargo distribution points that the multimodal transport logistics center intends to serve and the location of each cargo distribution point corresponding to the site selection plan.

[0063] C2. According to the location of the multimodal logistics center and the location of each cargo distribution point corresponding to the site selection plan, determine the distance between the multimodal logistics center and each cargo distribution point, and determine the average value of the distance between the multimodal logistics center and each cargo distribution point as the value of the proximity to the cargo distribution point corresponding to the site selection plan, expressed as:

[0064]

[0065] Among them, A31 represents the value of proximity to the cargo distribution point, L represents the total number of cargo distribution points that the multimodal logistics center intends to serve, and d l It represents the distance between the multimodal logistics center and the lth cargo distribution point, l = 1, 2, 3, ..., L, l represents the index of the cargo distribution point.

[0066] The support of trunk transport routes is to measure the proximity between the location of the multimodal logistics center and the trunk transport routes. The smaller the index value, the higher the support of the trunk transport routes.

[0067] In a possible implementation, for any site selection scheme, determining the value of the support of the trunk transportation line includes the following steps D1-D3:

[0068] D1. Obtain the total number of transportation modes involved in the multimodal logistics center corresponding to the site selection plan.

[0069] D2. Obtain the entrance location of the trunk transportation route closest to the multimodal logistics center corresponding to the site selection plan for each transportation mode.

[0070] D3. According to the location of the multimodal logistics center corresponding to the site selection plan and the entrance locations of the trunk transportation routes closest to the multimodal logistics center, determine the distance from the multimodal logistics center to each entrance location, and determine the average value of the distance as the value of the trunk transportation route support, expressed as:

[0071]

[0072] Among them, A 32 represents the support value of the trunk transport route, k represents the index of the transport mode involved in the multimodal transport logistics center, k = 1, 2, 3, ..., K, K represents the total number of transport modes involved in the multimodal transport logistics center, U k It represents the distance from the multimodal logistics center to the entrance of the trunk transportation route of the kth mode of transportation that is closest to the multimodal logistics center.

[0073] The average technical level of connecting roads is an indicator to measure the technical level of the road network connecting with the location of the multimodal logistics center. It can be quantified by the average technical level.

[0074] In a possible implementation, for any site selection scheme, determining the value of the average technical grade of the connecting roads includes the following steps E1 and E2:

[0075] E1. Obtain the total number of road grades connecting the multimodal logistics center corresponding to the site selection plan, as well as the length of each grade of road.

[0076] E2. According to the road grade and length of the road connecting the multimodal logistics center corresponding to the site selection plan, determine the value of the average technical grade of the connecting road, expressed as:

[0077]

[0078] Among them, A 33 represents the value of the average technical grade of the connecting roads, s represents the index of the road grade of the roads connecting to the multimodal logistics center, s=1,2,3,...,S, S represents the total number of road grades of the roads connecting to the multimodal logistics center, l s represents the length of the s-th level road connected to the multimodal logistics center, d s Indicates the technical level of the s-th level road connected to the multimodal logistics center.

[0079] The industrial coordination criterion is used to reflect the coordination between the proposed multimodal logistics center and the surrounding industries in terms of spatial layout, production supply and demand, etc. The corresponding indicators of the industrial coordination criterion include the development maturity of surrounding industries, market competition pressure and the impact of special enterprises.

[0080] The maturity of surrounding industry development is an indicator to measure the impact of the surrounding industries of the multimodal logistics center on the logistics business environment and the number of logistics cargo sources. Specifically, the number, scale, and development trend of the surrounding industries of the multimodal logistics center are examined to see whether they are conducive to the improvement of the logistics business environment, the formation of logistics agglomeration effects, and whether they can provide a long-term and sufficient supply of cargo for the logistics center. This indicator needs to be judged based on experience and can be quantified using the expert scoring method. The higher the maturity of the surrounding industry development, the greater the score of this indicator.

[0081] Market competition pressure is an indicator to measure the market competition pressure faced by the multimodal logistics center at the location of the multimodal logistics center. It can be quantified by expert scoring method. The smaller the market competition pressure, the higher the score of this indicator.

[0082] The impact of special enterprises is an indicator to measure the impact of special enterprises in the surrounding area on the construction and operation of the multimodal logistics center. Specifically, it refers to the extent to which the construction and operation of the multimodal logistics center may be adversely affected by energy, chemical and other hazardous goods enterprises and other special enterprises in the surrounding area. It can be quantified by the expert scoring method. The smaller the impact, the higher the score of this indicator.

[0083] The environmental adaptability criterion is used to reflect the mutual influence between nature, economy, society, environment and the construction, operation and development of multimodal logistics centers. The corresponding indicators of the environmental adaptability criterion include engineering construction conditions, impact on the surrounding environment and policy support.

[0084] Engineering construction conditions are indicators that measure the degree to which various engineering conditions required for the construction of a multimodal logistics center are met. Engineering construction conditions can be examined from four aspects: first, whether the natural conditions such as topography, geology, meteorology, and hydrology required for a multimodal logistics center are met; second, whether the conditions for access to municipal pipe networks such as water supply, power supply, gas, and communications are met; third, whether the conditions for sewage and rainwater collection, treatment, discharge, and garbage disposal are met; and fourth, whether existing municipal facilities, such as high-voltage corridors, thermal pipelines, and box culverts, will interfere with the construction of a multimodal logistics center. Expert scoring can be used for quantification. The better the engineering construction conditions, the higher the score of this indicator.

[0085] The impact on the surrounding environment is an indicator to measure the impact of the multimodal logistics center on the surrounding ecological and cultural environment. Specifically, it includes the impact on nature reserves, water sources, archaeological sites, historical and cultural protection areas, and the impact on the production and life of enterprises and residents. It can be quantified by expert scoring method. The smaller the impact on the surrounding environment, the higher the score of this indicator.

[0086] The policy support strength is an indicator to measure the degree to which the logistics industry support policies in the location selection area of ​​the multimodal logistics center are favorable to the logistics center. Specifically, it includes preferential policies in terms of regional land use, taxation, and subsidies. It can be quantified using the expert scoring method. The greater the policy support strength, the higher the score of this indicator.

[0087] Exemplarily, Table 1 is a multimodal transport logistics center site selection evaluation index system provided by the present invention, wherein the indicators of transportation route layout coordination, transportation route capacity adaptability, proximity to cargo distribution centers, trunk transportation route support and average technical level of connecting roads are quantitative indicators, and their actual index values ​​can be determined by quantitative evaluation. Other indicators are qualitative indicators, which can be qualitatively evaluated by expert scoring to obtain corresponding actual index values.

[0088] For qualitative indicators, for any qualitative indicator in any alternative solution, multiple experts score based on the preset scoring rules, and the average of multiple scoring results is determined as the actual value of the qualitative indicator. Exemplarily, the scoring rule can adopt a 10-point system, the better the performance, the higher the score, and only integer scores are given.

[0089] Table 1 Evaluation index system for location selection of multimodal logistics center

[0090]

[0091] The multimodal transport logistics center site selection evaluation method proposed in the present invention has constructed a site selection evaluation index system with 15 specific indicators in five aspects, including planning rationality, intermodal matching, distribution convenience, industrial coordination, and environmental adaptability. The system considers factors systematically and comprehensively, fully reflects the operational characteristics of the connection and coordination between different modes of transport in multimodal transport, and grasps the key to the site selection of multimodal transport logistics center projects. The proposed quantitative methods and comprehensive evaluation methods for each indicator are convenient and practical, and have both accuracy and operability. The site selection evaluation of the multimodal transport logistics center by this method can achieve the effect of saving work costs and working time while ensuring the accuracy of the results.

[0092] The following is a further detailed explanation with examples. Assume that the proposed multimodal transport logistics center is a road-rail transport logistics center, and its business is mainly the storage and transportation of coal and deep-processed products, and the storage and transportation of agricultural and sideline products and hardware and building materials will be added in the long term. The three site selection schemes P1, P2, and P3 are determined in advance, and the actual values ​​of the indicators corresponding to each site selection scheme are shown in Table 2:

[0093] Table 2 Actual values ​​and normalized values ​​of indicators corresponding to the site selection scheme

[0094]

[0095]

[0096] S103: Determine a first-level single-ranked weight vector and multiple second-level single-ranked weight vectors.

[0097] Among them, the first-level single-ranking weight vector is the hierarchical single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is the hierarchical single-ranking weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs.

[0098] Optionally, a hierarchical analysis method is used to determine a first-level single-order weight vector and multiple second-level single-order weight vectors.

[0099] Specifically include the following steps F1-F6:

[0100] F1. Establish a hierarchical model corresponding to the preset site selection evaluation index system.

[0101] F2. Use the 1-9 scaling method to establish a judgment matrix of the relative importance of the indicator layer to its criteria, and a judgment matrix of the relative importance of the criteria layer to the target layer.

[0102] Exemplarily, Table 3 is a relative importance judgment matrix of a criterion layer to a target layer provided by the present invention for the above example, and Tables 4 to 8 are relative importance judgment matrices of multiple indicator layers to their respective criteria provided by the present invention for the above example, as follows:

[0103] Table 3 Relative importance judgment matrix of criterion layer to target layer

[0104] S <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> <![CDATA[A4]]> <![CDATA[A5]]> <![CDATA[A1]]> / 1 / 5 1 / 2 3 1 / 3 <![CDATA[A2]]> / / 5 5 5 <![CDATA[A3]]> / / / 3 1 / 3 <![CDATA[A4]]> / / / / 1 / 3 <![CDATA[A5]]> / / / / /

[0105] Table 4 The relative importance judgment matrix of the indicator layer corresponding to the planning rationality criterion for the corresponding criterion

[0106]

[0107]

[0108] Table 5. Judgment matrix of the relative importance of the indicator layer corresponding to the intermodal matching criterion to the corresponding criterion

[0109] <![CDATA[A2]]> <![CDATA[A 21 ]]> <![CDATA[A 22 ]]> <![CDATA[A 23 ]]> <![CDATA[A 21 ]]> / 6 5 <![CDATA[A 22 ]]> / / 1 / 3 <![CDATA[A 23 ]]> / / /

[0110] Table 6 Judgment matrix of the relative importance of the indicator layer corresponding to the collection and distribution convenience criterion to the corresponding criterion

[0111] <![CDATA[A3]]> <![CDATA[A 31 ]]> <![CDATA[A 32 ]]> <![CDATA[A 33 ]]> <![CDATA[A 31 ]]> / 3 3 <![CDATA[A 32 ]]> / / 2 <![CDATA[A 33 ]]> / / /

[0112] Table 7 Judgment matrix of the relative importance of the indicator layer corresponding to the industrial coordination criterion to the corresponding criterion

[0113] <![CDATA[A4]]> <![CDATA[A 41 ]]> <![CDATA[A 42 ]]> <![CDATA[A 43 ]]> <![CDATA[A 41 ]]> / 3 1 / 3 <![CDATA[A 42 ]]> / / 1 / 4 <![CDATA[A 43 ]]> / / /

[0114] Table 8 Judgment matrix of relative importance of indicator layers corresponding to environmental adaptability criteria for their corresponding criteria

[0115] <![CDATA[A5]]> <![CDATA[A 51 ]]> <![CDATA[A 52 ]]> <![CDATA[A 53 ]]> <![CDATA[A 51 ]]> / 5 5 <![CDATA[A 52 ]]> / / 2 <![CDATA[A 53 ]]> / / /

[0116] Among them, S represents the target layer, A1 represents the planning rationality criterion, A2 represents the intermodal matching criterion, A3 represents the distribution convenience criterion, A4 represents the industry coordination criterion, A5 represents the environmental adaptability criterion, and A 11 A represents the compliance index of the upper planning. 12 represents the utilization index of existing facilities, A 13 represents the land scalability index, A 21 A represents the rationality index of the connection site setting. 22 A represents the coordination index of transportation route layout, 23 A represents the transport capacity adaptability index of the transport line. 31 A represents the proximity index to the cargo distribution center. 32represents the support index of the trunk transportation line, A 33 Indicates the average technical grade index of the connecting road, A 41 A represents the maturity index of surrounding industry development. 42 Indicates the market competition pressure index, A 43 represents the special enterprise impact index, A 51 Indicates the engineering construction condition index, A 52 Indicates the impact index on the surrounding environment, A 53 An indicator of the intensity of policy support.

[0117] F3. Calculate the maximum eigenvalue and corresponding eigenvector of the relative importance judgment matrix of the criterion layer to the target layer, and perform consistency check on the eigenvector. The eigenvector is the single-ranking weight vector of the first level.

[0118] Continuing with the above example, the maximum eigenvalue λ of the relative importance judgment matrix of the criterion layer to the target layer is calculated according to Table 3: max The summation method is used to determine the corresponding eigenvector W under the maximum eigenvalue: (0.0996, 0.5106, 0.1274, 0.0577, 0.2048). This eigenvector is the hierarchical single sorting weight vector of the criterion layer relative to the target layer. The consistency test of the hierarchical single sorting result is obtained, and the test coefficient CR is 0.0926, which is less than 0.1. It can be considered that the hierarchical single sorting result has passed the consistency test.

[0119] F4. Calculate the relative importance judgment matrix and corresponding eigenvector of the indicator layer to its criteria, and perform consistency check on the eigenvector. The eigenvector is the single-ranking weight vector of the second level.

[0120] Continuing with the above example, as shown in Table 9, the maximum eigenvalue of the relative importance judgment matrix of the indicator layer to the corresponding criterion is calculated according to Tables 4 to 8 respectively.

[0121] Table 9 Maximum eigenvalues ​​corresponding to Table 4-Table 8

[0122] Judgment Matrix <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> <![CDATA[A4]]> <![CDATA[A5]]> <![CDATA[λ max ]]> 3.0538 3.0958 3.0539 3.0741 3.0542

[0123] Then, the eigenvectors corresponding to the maximum eigenvalues ​​of the judgment matrix of the criterion to which the indicator layer shown in Table 9 belongs are calculated and shown in Table 10. The eigenvectors are multiple second-level single-ranking weight vectors.

[0124] Table 10 Corresponding eigenvectors of Table 9

[0125] Judgment Matrix Eigenvector <![CDATA[A1]]> (0.5247，0.1416，0.3338) <![CDATA[A2]]> (0.7071，0.0915，0.2014) <![CDATA[A3]]> (0.5889，0.2519，0.1593) <![CDATA[A4]]> (0.2721，0.1199，0.6080) <![CDATA[A5]]> (0.7028，0.1822，0.1149)

[0126] The consistency test is performed on the hierarchical single-ranking weight vector containing indicators under each criterion, and the test coefficient CR is shown in Table 11. The test coefficients under each criterion are all less than 0.1, and it can be considered that the above hierarchical single-ranking results have passed the consistency test.

[0127] Table 11. Consistency test coefficients corresponding to Table 10

[0128] Guidelines A1 A2 A3 A4 A5 CR 0.0517 0.0921 0.0518 0.0713 0.0521

[0129] F5. According to the calculation method of the total hierarchical ranking of the hierarchical analysis method, calculate the total hierarchical ranking weight vector of the indicator layer for the target layer, and perform a consistency check on it.

[0130] Continuing with the above example, as shown in Table 12, according to the calculation method of the hierarchical analysis method for the total hierarchical ranking, the total hierarchical ranking weight vector of the indicator layer for the target layer is calculated as follows.

[0131] Table 12 Total ranking weight vector of the indicator layer for the target layer

[0132] index <![CDATA[A 11 ]]> <![CDATA[A 12 ]]> <![CDATA[A 13 ]]> <![CDATA[A 21 ]]> <![CDATA[A 22 ]]> <![CDATA[A 23 ]]> <![CDATA[A 31 ]]> <![CDATA[A 32 ]]> Weight 0.0522 0.0141 0.0332 0.3610 0.0467 0.1028 0.0750 0.0321 index <![CDATA[A 33 ]]> <![CDATA[A 41 ]]> <![CDATA[A 42 ]]> <![CDATA[A 43 ]]> <![CDATA[A 51 ]]> <![CDATA[A 52 ]]> <![CDATA[A 53 ]]> Weight 0.0203 0.0157 0.0069 0.0351 0.1439 0.0373 0.0235

[0133] The further calculated consistency index test coefficient CR of the total hierarchical ranking is 0.0660, which is less than 0.1. It can be considered that the total hierarchical ranking has also passed the consistency test.

[0134] F6. If all consistency checks are passed, the hierarchical single-order weight vector of the corresponding criterion layer relative to the target layer is determined as the first hierarchical single-order weight vector, and the hierarchical single-order weight vector of the indicator layer for the criterion to which it belongs is determined as the second hierarchical single-order weight vector corresponding to the corresponding criterion.

[0135] The hierarchical single ranking result of the criterion layer for the target layer is the weight vector of the criterion layer for the target layer. The hierarchical single ranking result of the indicator layer for the criteria it belongs to is the weight vector of the indicator for the criteria it belongs to. The hierarchical total ranking result of the indicator layer for the target layer is the weight vector of the indicator layer for the target layer. Therefore, the weights of the multimodal logistics center location evaluation index system finally obtained based on the hierarchical analysis method are shown in Table 13.

[0136] Table 13 Weights of the multimodal logistics center location evaluation index system

[0137]

[0138] S104: Determine a target site selection scheme from multiple site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vector and each second-level single-ranking weight vector.

[0139] In a possible implementation, a target site selection scheme is determined from multiple site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vectors and each second-level single-ranking weight vector, including the following steps G1-G4:

[0140] G1. Based on the preset site selection evaluation index system, according to the actual values ​​of the indicators corresponding to each site selection plan and the second-level single-ranking weight vectors, a fuzzy comprehensive evaluation from the indicator layer to the criterion layer is performed on each site selection plan to obtain the first-level fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection plan.

[0141] Optionally, based on a preset site selection evaluation index system, according to the actual values ​​of the indicators corresponding to each site selection scheme and each second-level single-ranking weight vector, a fuzzy comprehensive evaluation from the indicator layer to the criterion layer is performed on each site selection scheme to obtain the first-level fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection scheme, including g1-g3:

[0142] g1. Normalize the actual values ​​of the indicators corresponding to each site selection scheme to obtain the normalized values ​​of the indicators corresponding to each site selection scheme.

[0143] Normalization can achieve the effect of unified dimension, which is convenient for comparative analysis.

[0144] Specifically, the normalization process for any indicator includes:

[0145] Assume that there are I site selection schemes. For any index m, let the index values ​​corresponding to the I site selection schemes be arranged in ascending order: (T1, T2, T3, …, T i ,…,T I ). After normalization, the I values ​​corresponding to the index m are expressed as: (t1, t2, t3, …, t i ,…,t I ).

[0146] Among them, for the "bigger the better" type indicators, the following formula is used for normalization:

[0147]

[0148] For the "smaller the better" type of indicators, the following formula is used for normalization:

[0149]

[0150] Among them, t i represents the value of the normalized index m corresponding to the i-th site selection scheme, i is the index of the site selection scheme, T max =max(T1,T2,T3,…,T i ,…,TI ), T min =min(T1,T2,T3,…,T i ,…,T I ).

[0151] Optionally, for any indicator, when the corresponding indicator values ​​of all site selection options are the same, they are all normalized to 1.

[0152] See Table 3 for the normalized results of the index values ​​corresponding to the three site selection options P1, P2, and P3 in the above example.

[0153] Through normalization processing, the index values ​​of different dimensions can be converted into values ​​between 0 and 1. At the same time, the "smaller the better" type of indicators can be reversely converted, that is, the smaller the actual indicator, the closer the normalized value is to 1, which is convenient for subsequent processing.

[0154] g2. Obtain the standard values ​​of each level in the preset evaluation set.

[0155] The setting of the evaluation level in the evaluation set can be set according to actual needs. For example, as shown in Table 14, the evaluation set includes five levels: excellent, good, medium, poor, and poor. Different levels correspond to different standard values, and the standard values ​​have been normalized and can be used to evaluate different indicators.

[0156] Table 14 Evaluation levels and standard values ​​of the evaluation set

[0157] excellent good middle Second-rate Difference 0.9 0.7 0.5 0.3 0.1

[0158] g3. Based on the ascending semi-trapezoidal membership function, the first-level evaluation fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection scheme is determined according to the normalized value of the indicator corresponding to each site selection scheme, the standard value of each level in the preset evaluation set and the second-level single-ranking weight vector.

[0159] Optionally, based on the ascending semi-trapezoidal membership function, according to the normalized values ​​of the indicators corresponding to each site selection scheme, the standard values ​​of each level in the preset evaluation set and each second-level single ranking weight vector, the first-level evaluation fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection scheme is determined, including:

[0160] 1. Based on the ascending semi-trapezoidal membership function, the membership matrix corresponding to each criterion is determined according to the normalized values ​​of the indicators corresponding to each site selection scheme and the standard values ​​of each level in the preset evaluation set.

[0161] Among them, the ascending semi-trapezoidal membership function is as follows Figure 3 As shown, its expression is:

[0162]

[0163] Where A(x) represents an ascending semi-trapezoidal membership function, x represents a variable, and a and b are constants.

[0164] Specifically, assuming that the evaluation set includes J evaluation levels, the evaluation set is represented in descending order of evaluation levels as follows: (V1, V2, …, V j ,…,V J ), the standard values ​​corresponding to the evaluation level from high to low are expressed as: (v1,v2,…,v j ,…,v J )(v j >v j+1 ). The membership vector of any site selection scheme relative to the evaluation set under a single indicator is expressed as: (r1, r2, …, r j ,…,r J ). Among them, the calculation formula of the membership degree of each indicator in the evaluation set is as follows:

[0165]

[0166]

[0167]

[0168]

[0169] Furthermore, by arranging the membership vectors of each site selection scheme under a single indicator in rows, the membership matrix under the criterion can be obtained.

[0170] Specifically, assuming that the goal of the site selection evaluation index system is A, the criterion layer includes N criteria, which can be expressed as: (Z1, Z2, …, Z n ,…Z N ). For different criteria, the corresponding number of indicators may be different. Criterion Z n Contains G indicators, expressed as: (C n1 ,C n2 ,…,C ng ,…C nG ). The corresponding indicator layer for criterion Z n The weight of the criterion Z n The corresponding second-level single-rank weight vector) is expressed as:

[0171] W n =(w n1 ,w n1 ,…,w ng ,…w nG ), and satisfies

[0172] Site selection plan based on criterion Zn Included indicators C ng Next, the membership vector of the evaluation set is expressed as: Then the site selection scheme is relative to the criterion Z n The membership matrix of the following indicators is expressed as:

[0173]

[0174] Continuing with the above example, the membership vectors of the indicators corresponding to the site selection schemes P1, P2 and P3 are shown in the corresponding horizontal contents in Tables 15 to 17.

[0175] Table 15 Membership vectors of each indicator corresponding to scheme P1

[0176]

[0177]

[0178] Table 16 Membership vectors of each indicator corresponding to scheme P2

[0179]

[0180] Table 17 Membership vectors of each indicator corresponding to scheme P3

[0181]

[0182] 2. According to each membership matrix and the corresponding second-level single-ranking weight vector, determine the first-level evaluation fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection plan.

[0183] Specifically, the “weighted average” fuzzy operator is used to calculate the criterion Z n The corresponding second-level single-rank weight vector and the site selection scheme in criterion Z n The membership matrix under fuzzy synthesis is used to obtain the criterion Z in the site selection scheme. n The corresponding first-level fuzzy comprehensive evaluation result is expressed as:

[0184]

[0185] Continuing with the above example, the first-level fuzzy comprehensive evaluation results corresponding to site selection options P1, P2 and P3 are shown in Tables 18 to 20.

[0186] Table 18 The first-level fuzzy comprehensive evaluation results corresponding to scheme P1

[0187]

[0188] Table 19 The first-level fuzzy comprehensive evaluation results corresponding to scheme P2

[0189]

[0190] Table 20 The first-level fuzzy comprehensive evaluation results corresponding to scheme P3

[0191]

[0192]

[0193] G2. According to the first-level fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection scheme, a membership matrix of the criterion layer corresponding to each site selection scheme to the target layer is constructed.

[0194] Specifically, the first-level fuzzy comprehensive evaluation results are normalized and formed into a matrix by rows to obtain the membership matrix of the criterion layer corresponding to the site selection scheme to the target layer.

[0195] Specifically, the criterion Z corresponding to the site selection plan n The first-level fuzzy comprehensive evaluation results (b n1 ,b n2 ,…,b nJ ) is normalized to obtain (B n1 ,B n2 ,…,B nJ );Then the normalized first-level fuzzy evaluation results are organized into a membership matrix of the criterion layer to the target layer by row, expressed as:

[0196]

[0197] G3. According to the membership matrix of the criterion layer corresponding to each site selection scheme to the target layer and the first-level single-ranking weight vector, a fuzzy comprehensive evaluation from the criterion layer to the target layer is performed on each site selection scheme to obtain the second-level fuzzy comprehensive evaluation vector corresponding to each site selection scheme.

[0198] Optionally, according to the membership matrix of the criterion layer corresponding to each site selection scheme to the target layer and the first-level single-ranking weight vector, a fuzzy comprehensive evaluation from the criterion layer to the target layer is performed on each site selection scheme to obtain a second-level fuzzy comprehensive evaluation vector corresponding to each site selection scheme, including:

[0199] The weighted average fuzzy operator is used to perform fuzzy synthesis on the membership matrix of the criterion layer corresponding to each site selection scheme to the target layer and the first-level single-ranking weight vector, and the second-level evaluation fuzzy comprehensive evaluation vector corresponding to each site selection scheme is obtained, which is expressed as:

[0200]

[0201] Among them, Q and (q1,q2,…,q J) represent the second-level fuzzy comprehensive evaluation vector corresponding to the site selection scheme, W=(W1,W2,…,W N ) represents the first-level single-rank weight vector, It represents the membership matrix of the criterion layer corresponding to the site selection scheme to the target layer, J is the total number of evaluation levels in the evaluation set, and N is the total number of criteria.

[0202] Through the first level fuzzy comprehensive evaluation, the membership vector of the indicator layer of the alternative scheme under each criterion layer is obtained. Through the second level fuzzy comprehensive evaluation, the membership vector of the alternative scheme under each criterion layer is solved as the final evaluation result.

[0203] Continuing with the above example, the first-level single-ranking weight vectors corresponding to schemes P1, P2, and P3 calculated from Table 3 are all:

[0204] W=[0.0996 0.5106 0.1273 0.0577 0.2048]

[0205] From the last column of Table 18, the fuzzy relationship matrix of the first-level fuzzy comprehensive evaluation result criterion layer corresponding to scheme P1 is:

[0206]

[0207] Then the fuzzy comprehensive evaluation result corresponding to the site selection scheme P1 is obtained as follows:

[0208] Q=W×B=[0.9448 0.0130 0.0102 0 0.0320].

[0209] From the last column of Table 19, the fuzzy relationship matrix of the first-level fuzzy comprehensive evaluation result criterion layer corresponding to scheme P2 is:

[0210]

[0211] Then the fuzzy comprehensive evaluation result corresponding to the site selection scheme P2 is obtained as follows:

[0212] Q=W×B=[0.0860 0 0.1580 0.3192 0.4368]

[0213] From the last column of Table 20, the fuzzy relationship matrix of the first-level fuzzy comprehensive evaluation result criterion layer corresponding to scheme P3 is:

[0214]

[0215] The fuzzy comprehensive evaluation result corresponding to the site selection scheme P3 is obtained as follows:

[0216] Q=W×B=[0.1747 0.0283 0.0587 0.0055 0.7328]

[0217] G4. Determine the scoring results corresponding to each site selection scheme based on the second-level fuzzy comprehensive evaluation vector corresponding to each site selection scheme and the scores of each level in the preset evaluation set, and determine the site selection scheme with the highest scoring result as the target site selection scheme.

[0218] The fuzzy comprehensive evaluation result of the location of the multimodal logistics center is the fuzzy vector of the membership of the alternative plan at each level of the evaluation set. When there are multiple alternative plans, a certain score can be assigned to each level in the evaluation set, and the fuzzy comprehensive evaluation result of the alternative plan is used as the weight vector, and the weighted average is performed with the scores of each level in the evaluation set to calculate the comprehensive score of the alternative plan. The alternative plan with the highest score can be used as the optimal location plan.

[0219] For example, the scores corresponding to each level in the evaluation set are as shown in Table 21:

[0220] Table 21 The corresponding scores of each level in the evaluation set

[0221] excellent good middle Second-rate Difference 5 4 3 2 1

[0222] Assume that the evaluation result of the i-th site selection scheme is: The calculation process of the comprehensive score of the site selection plan is:

[0223]

[0224] According to Table 21, different grades of scores are assigned to the comment set, and the fuzzy comprehensive evaluation results of the evaluation object are multiplied by the corresponding scores of each grade, and the final scores of the three schemes P1, P2, and P3 are: 4.84, 1.98, and 1.91. Scheme P1 has the highest score, so scheme P1 is used as the final recommended site selection scheme.

[0225] The method for selecting a multimodal logistics center site provided by the present invention obtains a plurality of multimodal logistics center site selection schemes; determines the actual values ​​of various indicators in a preset site selection evaluation index system corresponding to each site selection scheme, wherein the preset site selection evaluation index system includes a target layer, a criterion layer and an indicator layer in order from top to bottom, wherein the target layer includes a target, the criterion layer includes N criteria, and the indicator layer includes m indicators, wherein N and m are positive integers greater than 0, and m≥N; determines a first-level single-ranking weight vector and a plurality of second-level single-ranking weight vectors, wherein the first-level single-ranking weight vector is a hierarchical single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is a hierarchical single-ranking weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs; determines a target site selection scheme from a plurality of site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vector and the second-level single-ranking weight vectors, and can efficiently and accurately select a more reasonable multimodal logistics center layout address.

[0226] Figure 4 A schematic diagram of a multimodal transport logistics center site selection device provided by the present invention is shown in FIG. Figure 4 As shown, the device comprises:

[0227] The acquisition module 41 is used to acquire multiple multimodal transport logistics center site selection plans.

[0228] The processing module 42 is used to determine the actual value of each indicator in the preset site selection evaluation index system corresponding to each site selection scheme. The preset site selection evaluation index system includes a target layer, a criterion layer and an indicator layer from top to bottom. The target layer includes a multimodal logistics center mark, the criterion layer includes N criteria, and the indicator layer includes m indicators, wherein N and m are positive integers greater than 0, and m≥N.

[0229] The processing module 42 is also used to determine a first-level single-order weight vector and multiple second-level single-order weight vectors. The first-level single-order weight vector is a hierarchical single-order weight vector of the criterion layer relative to the target layer, and the second-level single-order weight vector is a hierarchical single-order weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs.

[0230] The processing module 42 is further used to determine a target site selection scheme from multiple site selection schemes according to the actual values ​​of the indicators corresponding to each site selection scheme and the first-level single-ranking weight vectors and each second-level single-ranking weight vector.

[0231] The present invention also provides a structural schematic diagram of an electronic device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus.

[0232] Memory, used to store computer programs;

[0233] The processor is used to implement the steps provided in the above method embodiment when executing the program stored in the memory.

[0234] The communication interface is used for communication between the above electronic device and other devices.

[0235] The method provided in the embodiment of the present invention can be applied to electronic devices. Specifically, the electronic device can be: a desktop computer, a portable computer, an intelligent mobile terminal, a server, etc. This is not limited here, and any electronic device that can implement the present invention belongs to the protection scope of the present invention.

[0236] The present invention also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps provided in the above method embodiment are implemented.

[0237] As for the device / electronic device / storage medium embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the specific content and beneficial effects and other related matters can be referred to the partial description of the method embodiment.

[0238] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0239] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for selecting a location for a multimodal logistics center, characterized in that: include: Obtain multiple multimodal logistics center site selection options; Determine the actual value of each indicator in the preset site selection evaluation indicator system corresponding to each site selection scheme, wherein the preset site selection evaluation indicator system includes a target layer, a criterion layer and an indicator layer from top to bottom, wherein the target layer includes a target, the criterion layer includes N criteria, and the indicator layer includes m indicators, wherein N and m are positive integers greater than 0, and m≥N; Determine a first-level single-ranking weight vector and a plurality of second-level single-ranking weight vectors, wherein the first-level single-ranking weight vector is a level-by-level single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is a level-by-level single-ranking weight vector of all indicators corresponding to any criterion relative to the criterion to which it belongs; A target site selection scheme is determined from the plurality of site selection schemes according to the actual values ​​of the indicators corresponding to the respective site selection schemes and the first-level single-ranking weight vectors and the respective second-level single-ranking weight vectors.

2. The method according to claim 1, characterized in that: The criteria include planning rationality criteria, intermodal matching criteria, distribution convenience criteria, industrial coordination criteria and environmental adaptability criteria; The planning rationality criterion is used to reflect the adaptability of the site selection of the multimodal logistics center to the superior planning, logistics facilities, and land supply conditions of the region where the site selection is located. The indicators corresponding to the planning rationality criterion include superior planning compliance, existing facility utilization, and land scalability. The superior planning compliance is an indicator that measures the degree of compliance between the site selection of the multimodal logistics center and the superior planning of the region where the site selection is located. The existing facility utilization is an indicator that measures the difficulty of connecting the multimodal logistics center with the existing logistics facilities. The land scalability is an indicator that measures the scalability of the spatial scale of the multimodal logistics center. The intermodal matching criterion is used to reflect the coordination and matching degree of different transport modes in terms of stations, routes and transport capacity based on the site selection of the multimodal logistics center. The indicators corresponding to the intermodal matching criterion include the rationality of the connection station setting, the coordination of the transportation line layout and the adaptability of the transportation line capacity. The rationality of the connection station setting is an indicator to measure whether the location of the existing station and port on which the multimodal logistics center relies is conducive to the connection and conversion of different transport modes. The coordination of the transportation line layout is an indicator to measure the coordination of the transportation line layout around the site selection of the multimodal logistics center. The transport line capacity adaptability is an indicator to measure the adaptability of the transport capacity of each transport mode line around the site selection of the multimodal logistics center and the future freight volume. The distribution convenience criterion is used to reflect the convenience of external transportation of the site selection of the multimodal logistics center. The indicators corresponding to the distribution convenience criterion include proximity to the cargo distribution point, support for trunk transportation lines and average technical level of connecting roads. The proximity to the cargo distribution point is an indicator that measures the distance between the site selection of the multimodal logistics center and the cargo distribution point. The support for trunk transportation lines is an indicator that measures the proximity between the site selection of the multimodal logistics center and the trunk transportation lines. The average technical level of connecting roads is an indicator that measures the technical level of the road network connected to the site selection of the multimodal logistics center. The industrial coordination criterion is used to reflect the coordination between the proposed multimodal logistics center and the surrounding industries in terms of spatial layout, production supply and demand, etc. The indicators corresponding to the industrial coordination criterion include the maturity of surrounding industrial development, market competition pressure and special enterprise impact. The maturity of surrounding industrial development is an indicator to measure the impact of the surrounding industries of the multimodal logistics center on the logistics business environment and the number of logistics cargo sources. The market competition pressure is an indicator to measure the market competition pressure faced by the multimodal logistics center at the location of the multimodal logistics center. The special enterprise impact is an indicator to measure the impact of special enterprises around the location on the construction and operation of the multimodal logistics center. The environmental adaptability criterion is used to reflect the mutual influence between nature, economy, society, environment and the construction, operation and development of intermodal logistics centers. The indicators corresponding to the environmental adaptability criterion include engineering construction conditions, impact on the surrounding environment and policy support. The engineering construction conditions are indicators that measure the degree to which various engineering conditions required for the construction of intermodal logistics centers are met. The impact on the surrounding environment is an indicator that measures the degree of influence of the intermodal logistics center on the surrounding ecological and cultural environment. The policy support is an indicator that measures the degree to which the logistics industry support policy in the location area of ​​the intermodal logistics center is beneficial to the logistics center.

3. The method according to claim 2, characterized in that For any of the site selection schemes, determining the value of the coordination of the transportation route layout includes: Obtain the total number of cargo distribution points that the multimodal transport logistics center corresponding to the site selection plan intends to serve and the location of each of the cargo distribution points; According to the location of the multimodal transport logistics center corresponding to the site selection scheme and the location of each of the cargo distribution points, the number of target cargo distribution points corresponding to the site selection scheme is determined, and the target cargo distribution points are cargo distribution points whose transportation routes between the multimodal transport logistics center corresponding to the site selection scheme and the multimodal transport logistics center meet preset conditions among all cargo distribution points corresponding to the site selection scheme; According to the total number of cargo distribution points corresponding to the site selection scheme and the number of the target cargo distribution points, the value of the coordination of the transportation route layout corresponding to the site selection scheme is determined, which is expressed as: Among them, A 22 It represents the value of coordination of transportation route layout, e represents the number of target cargo distribution points, and L represents the total number of cargo distribution points that the multimodal logistics center intends to serve.

4. The method according to claim 2 or 3, characterized in that: For any of the site selection schemes, determining the value of the transport capacity adaptability of the transport line includes: Obtaining the total number of transport modes involved in the multimodal transport logistics center corresponding to the site selection plan, the line transport capacity of each of the transport modes around the multimodal transport logistics center, and the predicted freight volume of each of the transport modes; The value of the transport capacity adaptability of the transport line corresponding to the site selection scheme is determined based on the total number of transport modes involved in the multimodal transport logistics center corresponding to the site selection scheme, the line transport capacity of each transport mode around the multimodal transport logistics center, and the predicted freight volume of each transport mode.

5. The method according to claim 2, characterized in that: For any of the site selection schemes, determining the value of the proximity to the cargo distribution point includes: Obtain the total number of cargo distribution points that the multimodal transport logistics center corresponding to the site selection plan intends to serve and the location of each of the cargo distribution points; According to the location of the multimodal transport logistics center and the location of each cargo distribution point corresponding to the site selection scheme, the distance between the multimodal transport logistics center and each cargo distribution point is determined, and the average value of the distance between the multimodal transport logistics center and each cargo distribution point is determined as the value of the proximity to the cargo distribution point corresponding to the site selection scheme, which is expressed as: Among them, A 31 represents the value of proximity to the cargo distribution point, L represents the total number of cargo distribution points that the multimodal logistics center intends to serve, and d l It represents the distance between the multimodal logistics center and the lth cargo distribution point, l = 1, 2, 3, ..., L, l represents the index of the cargo distribution point.

6. The method according to claim 2, characterized in that For any of the site selection schemes, determining the value of the support degree of the trunk transportation line includes: Obtaining the total number of transportation modes involved in the multimodal logistics center corresponding to the site selection plan; Obtaining the entrance location of the trunk transportation route closest to the multimodal transportation logistics center corresponding to the site selection plan for each of the transportation modes; According to the location of the multimodal transport logistics center corresponding to the site selection plan and the entrance location of each of the trunk transport routes closest to the multimodal transport logistics center, the distance from the multimodal transport logistics center to each of the entrance locations is determined, and the average value of the distance is determined as the support value of the trunk transport route, which is expressed as: Among them, A 32 represents the support value of the trunk transport route, k represents the index of the transport mode involved in the multimodal transport logistics center, k = 1, 2, 3, ..., K, K represents the total number of transport modes involved in the multimodal transport logistics center, U k It represents the distance from the multimodal transport logistics center to the entrance position of the trunk transport route of the kth mode of transport that is closest to the multimodal transport logistics center.

7. The method according to claim 2 or 3, characterized in that: For any of the site selection schemes, determining the value of the average technical grade of the connecting road includes: Obtaining the total number of road grades of roads connected to the multimodal logistics center corresponding to the site selection plan, and the length of each grade of road; According to the road grade and length of the road connecting the multimodal logistics center corresponding to the site selection plan, the value of the average technical grade of the connecting road is determined, which is expressed as: Among them, A 33 represents the value of the average technical grade of the connecting roads, s represents the index of the road grade of the roads connecting to the multimodal logistics center, s=1,2,3,...,S, S represents the total number of road grades of the roads connecting to the multimodal logistics center, l s represents the length of the s-th level road connected to the multimodal logistics center, d s Indicates the technical level of the s-th level road connected to the multimodal logistics center.

8. The method according to claim 1, characterized in that Determining a target site selection scheme from a plurality of site selection schemes according to the actual values ​​of the indicators corresponding to the site selection schemes and the first-level single-sorting weight vectors and the second-level single-sorting weight vectors includes: Based on the preset site selection evaluation index system, according to the actual value of the index corresponding to each site selection scheme and each second-level single-ranking weight vector, a fuzzy comprehensive evaluation from the index level to the criterion level is performed on each site selection scheme to obtain a first-level fuzzy comprehensive evaluation vector corresponding to each criterion in each site selection scheme; According to the first-level fuzzy comprehensive evaluation vector corresponding to each criterion in each of the site selection schemes, a membership matrix of the criterion layer corresponding to each of the site selection schemes to the target layer is constructed; According to the membership matrix of the criterion layer corresponding to each of the site selection schemes to the target layer and the first-level single-ranking weight vector, a fuzzy comprehensive evaluation from the criterion layer to the target layer is performed on each of the site selection schemes to obtain a second-level fuzzy comprehensive evaluation vector corresponding to each of the site selection schemes; According to the second-level fuzzy comprehensive evaluation vector corresponding to each of the site selection schemes and the scores of each level in the preset evaluation set, the scoring results corresponding to each of the site selection schemes are determined, and the site selection scheme with the highest scoring result is determined as the target site selection scheme.

9. A device for selecting a location for a multimodal logistics center, characterized in that: include: An acquisition module, used to acquire multiple multimodal logistics center site selection plans; A processing module, used to determine the actual value of each indicator in the preset site selection evaluation indicator system corresponding to each site selection scheme, wherein the preset site selection evaluation indicator system includes a target layer, a criterion layer and an indicator layer from top to bottom, wherein the target layer includes a target, the criterion layer includes N criteria, and the indicator layer includes m indicators, wherein N and m are positive integers greater than 0, and m≥N; The processing module is further used to determine a first-level single-ranking weight vector and a plurality of second-level single-ranking weight vectors, wherein the first-level single-ranking weight vector is a level-by-level single-ranking weight vector of the criterion layer relative to the target layer, and the second-level single-ranking weight vector is a level-by-level single-ranking weight vector of all indicators corresponding to any of the criteria relative to the corresponding criteria; The processing module is further used to determine a target site selection scheme from the multiple site selection schemes according to the actual values ​​of the indicators corresponding to each of the site selection schemes and the first-level single-sorting weight vectors and each of the second-level single-sorting weight vectors.

10. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing any of the methods described in claims 1-8 when executing a program stored in a memory.

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