Method and system for planning and designing port-approaching logistics park

Abstract

The invention discloses a port-adjacent logistics park planning and design method and system, and belongs to the technical field of port logistics planning and engineering informationization, and the method comprises the steps: generating a plurality of sets of port-adjacent logistics park parameterized plane models, and outputting m sets of park planning and design schemes and corresponding unit parameter data sets; calculating the annual workload and the average stockpiling day number of different types of goods, and outputting a goods quantity statistical result; calculating sub-item cost and engineering cost of each plane unit, and calculating other cost and reserve cost of engineering construction so as to obtain and output total investment of the engineering; calculating the sub-item incomes of the storage unit and the storage yard unit, and correcting the sub-item incomes according to the comprehensive influence factors to obtain the expected income of each set of planning and design scheme; and determining the planning design scheme with the minimum cost-to-benefit ratio as an optimal scheme. According to the method, layout generation, cargo volume prediction, cost calculation and income comparison and selection can be completed at the same time in the planning stage, and the problems that traditional planning design is low in efficiency and lacks economical linkage analysis are effectively solved.

Description

Technical Field

[0001] This invention belongs to the field of port logistics planning and engineering information technology, and in particular relates to a planning and design method and system for port logistics parks. Background Technology

[0002] With the continuous expansion of port integrated service functions, port-adjacent logistics parks are gradually becoming comprehensive logistics nodes integrating warehousing, storage yards, supporting facilities, and traffic organization. Traditional logistics park planning and design mainly rely on manual experience for scheme drawing and area allocation. The layout parameters of each plan unit, building spacing, and storage yard area are usually obtained through manual calculation and experience correction.

[0003] This approach suffers from several problems, including a disconnect between design and economic evaluation, low efficiency in scheme iteration, a lack of multi-scheme comparison and automatic optimization mechanisms, and fragmented data management. The planning and design phase often focuses solely on spatial layout, while engineering costs and operational benefits are typically estimated manually later, resulting in a lack of real-time correlation between design results and economic analysis. When site conditions, functional proportions, or planning indicators are adjusted, it is necessary to redraw the scheme and recalculate area, cost, and revenue, a process that is lengthy and involves significant repetitive work. Furthermore, existing design tools cannot automatically generate multiple layout schemes that meet constraints, nor can they achieve objective optimization based on economic indicators. Floor plan design, quantity calculation, cost estimation, and economic analysis are typically distributed across different software systems, resulting in information silos, inconsistent data interfaces, and difficulty in achieving parametric linkage.

[0004] Therefore, how to establish a technical method that integrates geometric modeling, cargo volume calculation, cost analysis and economic evaluation during the planning stage, so as to achieve automatic generation of park schemes and optimal cost-benefit comparison, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a planning and design method and system for port logistics parks, in order to solve the technical problem mentioned in the background art of how to establish a technical method that can integrate geometric modeling, cargo volume calculation, cost analysis and economic evaluation in the planning stage, and to solve the technical problem of how to automatically generate park plans and select the most cost-effective option.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A planning and design method for port-adjacent logistics parks includes:

[0008] Based on the set geometric and associated parameter constraints, the parametric modeling program is called to generate multiple parametric planar models of the port logistics park that meet the constraints, and outputs m sets of park planning and design schemes and the corresponding unit parameter datasets for each scheme, where m is a positive integer;

[0009] Based on the unit parameter dataset, establish a quantitative mapping relationship from area parameters to storage volume and from storage volume to annual workload, calculate the annual workload and average storage days for different types of goods, and output the cargo volume statistics.

[0010] Based on the unit parameter dataset, and using the preset unit area cost index, the itemized cost and engineering expenses of each planar unit are calculated, and other construction costs and contingency funds are further calculated to obtain and output the total project investment.

[0011] The revenue of the storage unit and the yard unit is calculated based on the cargo volume statistics, and the revenue of the unit is adjusted according to the comprehensive impact factor to obtain the expected revenue of each planning and design scheme.

[0012] The cost-benefit ratio is calculated based on the total investment and expected benefits of each scheme. Based on the cost-benefit ratio, the planning and design scheme with the smallest cost-benefit ratio is selected as the preferred scheme from the m planning and design schemes. The preferred scheme and the corresponding total investment, expected benefits and sub-item benefits are then output.

[0013] Preferably, the planar unit includes a storage unit, a storage yard unit, a road unit, ancillary building units, a greening unit, and other units.

[0014] Preferably, the associated parameters include: plot ratio, building setback distance from road, building setback distance from land boundary, building setback distance from wall, fire separation distance between buildings, fire separation distance between building and storage yard, area of ​​supporting building unit, area of ​​green space unit, and area of ​​other units.

[0015] Preferably, the unit parameter dataset corresponding to each planning and design scheme includes: the number and total area of ​​each type of storage sub-unit, the number and total area of ​​the storage yard sub-unit, the total length and total area of ​​each type of road sub-unit, the area of ​​supporting building units, the area of ​​greening units, and the area of ​​other units.

[0016] Preferably, the annual workload is calculated based on the storage volume per unit area, area utilization rate, imbalance coefficient and average storage days, and is obtained by establishing a quantitative mapping relationship between area parameters and storage volume.

[0017] Preferably, the sub-itemized revenue includes annual revenue calculated based on the workload of the storage unit and / or yard unit, the average storage days, and the corresponding unit charge parameters.

[0018] Preferably, the comprehensive impact factor is expressed as A = x·f·r·p, where x represents the project nature impact factor, f represents the risk situation impact factor, r represents the financing cost impact factor, and p represents the operator's historical preference identification factor.

[0019] A port logistics park planning and design system, comprising:

[0020] One or more processors;

[0021] A storage device for storing computer program instructions for performing the above methods;

[0022] When the one or more computer program instructions are executed by the one or more processors, the one or more processors perform the method described above.

[0023] It also includes: a layout generation module, a cargo quantity calculation module, a cost calculation module, and a benefit analysis module.

[0024] The layout generation module is used to generate multiple sets of parametric planar models of the port logistics park that meet the constraints based on the set geometric parameter constraints and associated parameter constraints, and output m sets of park planning and design schemes and the corresponding unit parameter datasets for each scheme, where m is a positive integer.

[0025] The cargo volume calculation module is used to establish a quantitative mapping relationship from area parameters to storage volume and from storage volume to annual workload based on the unit parameter dataset, calculate the annual workload and average storage days of different types of goods, and output cargo volume statistics results.

[0026] The cost calculation module is used to calculate the itemized cost and engineering expenses of each planar unit based on the unit parameter dataset and the preset unit area cost index, and further calculate other construction costs and contingency funds, thereby obtaining and outputting the total investment of the project.

[0027] The benefit analysis module is used to calculate the sub-item revenue of the storage unit and the yard unit based on the cargo volume statistics, and to correct the sub-item revenue according to the comprehensive impact factor to obtain the expected revenue of each planning and design scheme; to calculate the cost-benefit ratio based on the total engineering investment and expected revenue of each scheme, and to determine the planning and design scheme with the smallest cost-benefit ratio from m planning and design schemes as the preferred scheme based on the cost-benefit ratio, and to output the preferred scheme and the corresponding total engineering investment, expected revenue and sub-item revenue results.

[0028] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0029] A computer program product includes a computer program that, when executed by a processor, implements the steps of the above-described method.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] The planning and design method and system for port logistics parks proposed in this invention achieves coordinated optimization from spatial design to economic analysis through parametric modeling and automated calculation. It can simultaneously complete layout generation, cargo volume prediction, cost calculation and benefit comparison during the planning stage, thereby effectively solving the problems of low efficiency and lack of economic linkage analysis in traditional planning and design.

[0032] This invention automatically generates multiple park layout schemes under land boundary conditions and planning design constraints through a parametric modeling program, and outputs the corresponding unit parameter datasets for each scheme. Based on this, it correlates area parameters with cargo volume calculation parameters, cost index parameters, and unit fee parameters to automatically calculate workload and average storage days, itemized costs and total project investment, as well as itemized revenue and revenue evaluation parameters. Furthermore, it calculates the cost-benefit ratio to achieve automatic comparison and selection of multiple schemes. Compared with existing methods that rely on manual reverse mapping, decentralized statistics, and manual summarization, this invention can continuously execute layout generation, cargo volume statistics, cost calculation, and scheme evaluation calculation under a unified data interface, reducing errors caused by manual input, unit conversion, and intermediate steps. It also automatically updates the calculation results of each scheme when constraints or input parameters change, thereby improving the efficiency and consistency of scheme generation and evaluation calculations. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the method flow of a preferred embodiment of the present invention;

[0034] Figure 2 This is a schematic diagram of the method flow of the first preferred embodiment of the present invention;

[0035] Figure 3 This is a schematic diagram of a parametric planar model according to a preferred embodiment of the present invention;

[0036] Figure 4 This is a schematic diagram of the system structure of a preferred embodiment of the present invention. Detailed Implementation

[0037] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0038] To facilitate standardized calculation and comparison of area parameters, storage capacity, cost, and benefits for the parametric plan model of the Lingang Logistics Park, in all embodiments of this invention, the storage units are set up as single-story warehouses (number of floors = 1). Therefore, the building area of ​​the storage unit is consistent with its land area. At the same time, in the parametric plan model of the Lingang Logistics Park generated by the parametric modeling program, the area parameters of each plan unit (including storage units, storage yard units, road units, supporting building units, greening units, and other units) are all land area (planar projected area). Unless otherwise specified, the "area / area parameters" involved in subsequent steps shall be based on the above-mentioned land area.

[0039] like Figures 1-4 As shown:

[0040] First preferred embodiment:

[0041] This embodiment provides a planning and design method for a port-adjacent logistics park, including the following steps:

[0042] S100, based on the set geometric parameter constraints and associated parameter constraints, calls the parametric modeling program to generate multiple sets of parametric planar models of the port logistics park that meet the constraints, and outputs m sets of park planning and design schemes and the corresponding unit parameter datasets for each scheme, where m is a positive integer.

[0043] S101. Based on the land boundary and functional requirements, determine the geometric parameters of the planar units in the parametric planar model of the Lingang Logistics Park, which will be used to constrain the unit layout and combination relationships in the subsequent parametric modeling process.

[0044] The planar unit includes storage units, storage yard units, road units, supporting building units, greening units, and other units.

[0045] To ensure that the subsequent parametric generation process meets the requirements of engineering specifications, fire protection specifications, and logistics operation processes, the preferred geometric parameter constraints for each unit in this step are set as follows:

[0046] For storage units, the maximum floor area, depth, and width of a single-story warehouse are determined according to fire safety regulations and logistics operation processes to limit the geometric range generated during parametric modeling. To adapt to the modular and standardized requirements of the park planning, several types of storage sub-units can be pre-defined, including the first storage unit J1, the second storage unit J2, ..., the nth type of storage unit J... n。 For example, for a Class C single-story warehouse in a port logistics park, its floor area shall not exceed 24,000 m². 2The depth shall not exceed 120 m and the maximum width shall be 200 m; furthermore, when the storage sub-unit is a Class C single-story warehouse, the length and width parameters can be selected in the range of approximately 70 m × 100 m to 120 m × 200 m.

[0047] For yard units, standardized yard sub-units are set up according to the container stacking layout and operation access requirements. For example, the length and width parameters of the yard sub-unit can be set to approximately 200 m × 100 m, and the net distance between adjacent yard sub-units should not be less than 10 m to meet the operation requirements of container handling equipment.

[0048] For road units, width parameters are determined based on the functional classification of roads within the park, dividing roads into arterial roads, secondary arterial roads, and fire truck access roads. The widths of arterial and secondary arterial roads are selected according to the requirements for road width in the "Code for Fire Protection Design of Buildings" and the "Code for Overall Design of Harbors". Specifically, the width L1 of arterial roads is in the range of 15 to 30 m, the width L2 of secondary arterial roads is in the range of 9 to 15 m, and the net width L3 of fire truck access roads should not be less than 4 m.

[0049] The supporting building units are used to accommodate auxiliary functions such as offices, waiting areas, and power distribution. Their area is determined according to 5% to 10% of the total land area W of the park. They are set in accordance with the control requirements for the proportion of land for supporting service buildings in the "Logistics Building Design Code" and are not subject to geometric parameter constraints.

[0050] The green area is determined according to the approved green space ratio of the land parcel. For example, when the approved green space ratio is 10% to 20%, the value can be determined based on the land use intensity of the park, such as W×10%, without geometric parameter constraints.

[0051] Other units are the parts within the logistics park excluding warehousing units, storage yard units, road units, supporting building units, and greening units, and are not subject to geometric parameter constraints.

[0052] S102, Based on the above unit parameters, further set associated parameters for the park plan model to control the layout logic of the model during the parametric generation process.

[0053] The associated parameters include the total land area W of the park, the plot ratio r, the building setback distance from the road s1, the building setback distance from the land boundary s2, the building setback distance from the wall s3, the fire separation distance between buildings s4, the fire separation distance between buildings and the storage yard s5, the area of ​​the supporting building unit P1, the area of ​​the greening unit G1, and the area of ​​other units Q1.

[0054] The total land area W and plot ratio r of the park are obtained through the planning indicators approved for the land parcels.

[0055] Building setback distance from road s1: In port-adjacent industries, the building setback distance from road s1 ranges from 1.5 to 6 meters. The building setback distance from road s1 can be determined based on the nature of the land plot and traffic demand. Typical values ​​are shown in Table 1.

[0056] Table 1 Reference Table for Building Setback Distance s1 from Road

[0057]

[0058] Building setback distance s2 from land boundary: In practical engineering applications, the minimum setback distance of a building from the land boundary is usually controlled by the local urban and rural construction authorities in accordance with regional planning management technical regulations. Considering the characteristics of the port logistics park warehouse buildings involved in this embodiment as low-rise non-residential buildings, the range of values ​​for the building setback distance s2 from the road can be determined by referring to the relevant setback standards for low-rise non-residential buildings in local technical regulations. Specifically, when the land boundary coincides with or overlaps with the planned road red line, s2 can also represent the distance of the building from the surrounding planned road red line. For example, considering the layout requirements of the warehouse buildings and fire evacuation requirements, s2 can be set in the range of 5–10 m; 8–10 m can be taken on the side closer to the main road, and 5–8 m can be taken on the side closer to the secondary road or branch road, but it is not limited to these limits.

[0059] The distance s3 between the building's exterior wall and the perimeter wall: According to the "Minimum Clear Distance between the Edge of the Building's Exterior Wall and the Edge of the Perimeter Wall" requirement in the "General Design Code for Seaports," the clear distance between the exterior wall of the warehouse building and the perimeter wall of the industrial park should not be less than 1.0m. Based on the safety clearance requirements between the perimeter wall and the building's exterior wall, as well as the requirements for inspection, maintenance, and pipeline layout, the distance s3 between the warehouse building's exterior wall and the perimeter wall can be constrained to avoid restrictions on work, maintenance, and emergency evacuation on the perimeter wall side. For example, s3 can be set to not less than 1.0m, with a typical value of 1.0 to 1.5m, but not limited to this.

[0060] Fire separation distance s4 between buildings: The fire separation distance s4 between buildings is set separately for the short and long sides of the buildings. The short side distance mainly meets fire separation requirements and is set to be no less than 10m. For the long side, due to the need to arrange loading and unloading platforms, parallel parking spaces, and central main roads, according to the "Logistics Building Design Code" and the combination relationship of "platform to road edge line approximately 19-24 m, main road width approximately 9-30 m" in typical layouts, the functional distance between the long sides of two warehouse buildings is usually in the range of 45-55 m. For example, in a layout scenario that meets the efficiency of vehicle parking and passage, the distance between the long sides of the buildings can be set to approximately 50 m. The above values ​​are only examples and can be adjusted according to the platform type, road grade, and traffic organization method.

[0061] Supporting building unit area P1: In this embodiment, the supporting building unit area P1 is used to accommodate office, waiting area, power distribution, and other auxiliary facilities in the park. Its area ratio must meet the land use control requirements for supporting service buildings in the logistics park planning. According to the control indicators for logistics building land use structure in the "Logistics Building Design Code," the land area of ​​supporting service buildings should preferably account for 5% to 10% of the total land area of ​​the logistics park. For example, the land area of ​​the supporting building unit can be set to 5% to 10% of the total land area W of the park to meet both regulatory control and the park's auxiliary functional needs. The above ratio range can be adjusted according to local standards, park level, and functional configuration.

[0062] Green space unit area G1: This represents the green area within the logistics park used for landscaping and ecological regulation. The green area typically needs to meet the green space ratio requirements specified in the land parcel approval document. However, planning departments in different regions may set different green space ratio control indicators for logistics land. Therefore, this embodiment sets the green space unit area G1 as a value determined proportionally based on the green space ratio specified in the land parcel approval document, without limiting specific administrative division requirements. For example, if a land parcel approval document requires a green space ratio of 10% to 20% for logistics land, an appropriate percentage can be selected within this range based on the park's functional needs and land use efficiency, such as taking the minimum value of 10% to improve production land efficiency. If the land parcel approval directly stipulates a fixed green space ratio, such as 15%, it can be calculated as G1 = W × 15%. This method ensures that the green area meets planning review requirements while also being coordinated with the park's spatial utilization efficiency.

[0063] The area of ​​other units, Q1, is the portion within the logistics park excluding warehousing units, storage yard units, road units, supporting building units, and green space units.

[0064] After setting the aforementioned related parameters, a logical node model is constructed using a parametric geometric modeling platform, and the constraints and geometric combinations of each parameter are set. Subsequently, a script program calls the node interface of the modeling platform, performs iterative loops and conditional judgments based on different input parameters, and automatically generates multiple park layout schemes that meet the constraints. Based on automatic generation, the relative positions, orientations, and combination relationships of storage units and yard units can be manually fine-tuned in a visual interface. During the adjustment process, the system verifies the standard constraints and updates the area parameter data in real time.

[0065] S103, call the parametric modeling program to generate multiple sets of parametric planar models of the Lingang Logistics Park that meet the constraints.

[0066] First, the combination relationship of different units is controlled by conditional statements, and the script program is called to drive the modeling platform to perform loop iterations and automatically generate multiple park layout schemes that meet the constraints.

[0067] Specifically, in the parametric modeling platform, if conditional statements are set up to automatically select or adjust the layout combination relationships of storage units, storage yard units, road units, supporting building units, greening units and other units based on different input parameters (such as plot shape, functional proportion, road connection relationship, building setback requirements, etc.) to generate a park layout that meets the constraints.

[0068] The automatic generation process can also be achieved using scripts. Specifically, a Python script can call the node interface of the parametric modeling platform to perform loop assignments and conditional calculations on each input variable, driving the modeling program to automatically output multiple park layout schemes.

[0069] Manual optimization can also be performed on top of the automatically generated layout. Specifically, the relative positions, orientations, and combinations of storage units and yard units can be fine-tuned in the visual interface. While making adjustments, the system verifies various regulatory constraints and updates area parameters in real time. Through joint optimization by manual and program methods, the generated overall layout of the park is ensured to meet both planning specifications and actual engineering conditions.

[0070] Through the above steps, several planning and design schemes for the port logistics park, S1, S2, ..., S1, are obtained, which meet the planning requirements and functional needs. m There are a total of m sets, and the unit parameter dataset corresponding to each planning and design scheme includes:

[0071] The number of each type of storage sub-unit is denoted as a. 1m a 2m ... a nm ; respectively corresponding to the first storage unit J1, the second storage unit J2, ..., the nth storage unit J n Quantity;

[0072] Total area J of each type of storage sub-unit 1m J 2m ... J nm ; respectively corresponding to the first storage unit J1, the second storage unit J2, ..., the nth storage unit J n The total area;

[0073] The number of storage yard sub-units is denoted as b. 1m ;

[0074] Total area D of the storage yard sub-unit 1m ;

[0075] The total length of each type of road sub-unit is denoted as c. 1m c 2m c 3m These correspond to the total lengths of main roads, secondary roads, and fire lanes, respectively.

[0076] The total area of ​​each type of road sub-unit is denoted as L. 1m L 2m L 3m These correspond to the total area of ​​the main roads, secondary roads, and fire lanes, respectively.

[0077] Supporting building unit area P 1m ;

[0078] Green unit area G 1m ;

[0079] The area Q of other units 1m Q1=WJ 1m -J 2m -J 3m -……-J nm -D 1m -L 1m -L 2m -L 3m -P 1m -G 1m ,

[0080] Where W is the total land area of ​​the park, m represents the number of the m-th park planning and design scheme, and n represents the sequence number of different planar units within the scheme.

[0081] Using the above method, the area parameters of each of the m park planning and design schemes can be calculated to obtain the unit parameter dataset of the m schemes, which can be used as input conditions for subsequent cargo volume calculation, cost calculation and benefit analysis.

[0082] S200 establishes a quantitative mapping relationship from area parameters to storage volume and from storage volume to annual operating volume based on data in the planning and design scheme of the Lingang Logistics Park. It calculates the annual operating volume and average storage days for different types of goods and outputs cargo volume statistics. It realizes data linkage between spatial planning results and logistics capacity calculation.

[0083] For a storage sub-unit, the amount of goods stored is determined based on the sub-unit's area, the characteristics of the goods, and the operational organization method. For the nth type of storage sub-unit, the area parameter J... nm Given the information, the quantity of goods stored is determined according to the following formula:

[0084]

[0085] in, This represents the total area of ​​the nth type of storage sub-unit in the mth scheme; The storage capacity per unit area for this type of goods is selected from empirical values ​​or industry databases based on the type of goods and stacking method. The area utilization rate is typically in the range of 0.6 to 0.7, determined based on the cargo stacking process and the proportion of aisles within the warehouse.

[0086] In obtaining the stockpile Then, the annual workload of the nth type of storage sub-unit can be calculated. The formula for calculating annual workload is:

[0087] ;

[0088] in, The number of annual operating days for the logistics park is selected based on the park's operating procedures, with an optimal range of 350 to 365 days. This refers to the average number of days that goods are stored in this type of storage subunit, determined based on the goods turnover cycle, storage attributes, or industry statistics. This is the imbalance coefficient, used to reflect the difference between peak and valley operations. For logistics parks, it is usually taken as 1.1 to 1.9.

[0089] For yard sub-units, the storage volume is determined based on the container stacking process and area size. Yard storage volume The annual operational volume is calculated based on the number of standard containers it can accommodate, the number of stacked layers, and the volume utilization rate, and is used as the basis for determining the annual operational volume of the storage yard. The calculation formula is:

[0090] ;

[0091] ;

[0092] in, The container yard inventory (in TEUs). The number of ground containers in a yard unit. To maximize the utilization of the storage yard area, This refers to the number of stacking heights in the storage yard. This represents the average number of days containers are stored, and the value is determined based on operational needs. This is the container handling imbalance coefficient, selected based on historical throughput fluctuations.

[0093] Through the above steps, the annual workload of each type of warehousing sub-unit in the m-th scheme can be obtained respectively. Annual handling volume of the storage yard and the corresponding average storage days , This forms the corresponding cargo volume dataset. To ensure the model's recomputability and parameter transparency, intermediate quantities (including...) are saved synchronously during the calculation process. , (etc.) and the parameter values ​​used , , , , These data can be directly accessed for subsequent cost calculations, benefit assessments, and sensitivity analyses, enabling automated data linkage between planning, capacity, and economic efficiency.

[0094] S300 receives the unit parameter dataset from the planning and design scheme of the Lingang Logistics Park, calculates the itemized cost and engineering expenses of each planar unit based on the preset unit area cost index, and further calculates other construction costs and contingency funds to obtain and output the total project investment; using the unit parameter dataset and drainage unit area PS output by S100... 1m With the area of ​​the power supply lighting unit GD 1m As input, since the drainage unit and power supply and lighting unit are auxiliary facilities, this embodiment sets their area to be the same as the area D of the storage yard unit. 1m Consistent.

[0095] As the basis for cost calculation, the unit area cost index of each planar unit is determined using the market-based engineering data method, including: storage unit cost indexes JZ1, JZ2, ..., JZ n The unit cost indices are as follows: DZ for storage yards, LZ1, LZ2, and LZ3 for roads, PZ for supporting buildings, GZ for landscaping, QZ for other units, PSZ for drainage, and GDZ for power supply and lighting. These unit cost indices are based on those published by government departments and local cost management agencies, and have been adjusted using engineering software and empirical parameters.

[0096] S301, Sub-unit project cost calculation;

[0097] In the cost calculation process, the engineering cost of each sub-unit is first calculated separately.

[0098] Warehouse building cost A m The cost is calculated based on the formula: "Warehouse building cost = warehouse unit area × warehouse unit area cost index".

[0099] Yard construction cost B m The cost of the storage yard is calculated as follows: "Storage yard unit area × storage yard unit area index".

[0100] Road construction cost C m Calculated according to "Road construction cost = Road unit area × Road unit area cost index";

[0101] Greening cost D m The cost of greening is calculated as follows: "Greening cost = Greening unit area × Greening unit area cost index";

[0102] Supporting building E mThe construction cost is calculated as follows: "Construction cost of supporting buildings = Area of ​​supporting building unit × Cost index per unit area of ​​supporting buildings";

[0103] Other construction costs F m Calculated according to "Other costs = Area of ​​other units × Cost index of other unit areas";

[0104] Drainage construction cost G m Calculated according to "Drainage cost = Drainage unit area × Drainage unit area cost index";

[0105] Power supply for lighting H m The cost is calculated as follows: "Power supply and lighting cost = power supply and lighting unit area × power supply and lighting unit area cost index".

[0106] By calculating the costs mentioned above, the total project cost for scheme m is obtained:

[0107] ;

[0108] To ensure consistency of the dimensions of each product, the measurement units of the area parameters and the unit cost index are checked for consistency before the calculation is performed. If any missing or out-of-bounds input parameters are found, the confirmed default index is used for rollback, and the rollback value is written into the calculation record for traceability.

[0109] S302, upon receiving project costs Next, other construction costs will be calculated. With contingency fund In order to obtain the total investment of the complete project.

[0110] Other construction costs shall be calculated as follows:

[0111] ;

[0112] The comprehensive fee rate X is generally selected within the range of 15% to 20% based on industry experience and historical project statistics.

[0113] Contingency funds are calculated as follows:

[0114] ;

[0115] Therefore, the total investment for scheme m can be obtained as follows:

[0116] ;

[0117] S303 outputs the complete cost result set corresponding to scheme m, including:

[0118] Cost of each sub-unit project: A m B m Cm D m E m F m G m H m ;

[0119] Project Costs: ;

[0120] Other construction costs: ;

[0121] Contingency Fund: ;

[0122] Total project investment: ;

[0123] It also outputs the unit cost index used, its source label, and correction coefficient, and retains the intermediate calculation results of the itemized costs for subsequent economic analysis, sensitivity analysis, and batch recalculation.

[0124] S400: Calculate the sub-item revenue of warehousing unit and yard unit based on cargo volume statistics, and adjust the sub-item revenue according to comprehensive impact factors to obtain the expected revenue of each planning and design scheme; calculate the cost-benefit ratio based on the total engineering investment and expected revenue of each scheme, and determine the planning and design scheme with the smallest cost-benefit ratio from the m schemes as the preferred scheme based on the cost-benefit ratio, and output the preferred scheme and its corresponding total engineering investment, expected revenue and sub-item revenue results.

[0125] Before calculating the revenue, the system first calculates the total project investment obtained from the cost calculation. As a cost-side input, the annual workload and average storage days parameters output by the cargo volume statistics module are also included. 1m JT 1m}、{JL 2m JT 2m}、……、{JL nm JT nm} and container yard parameters {DL m DT 1m This serves as the foundational data for the revenue side, and includes unit pricing parameters collected based on market research or external data interfaces. These unit pricing parameters include: the unit storage fee rate corresponding to the nth type of storage sub-unit. and the unit storage fee rate corresponding to the storage yard unit .

[0126] To ensure consistency of units in subsequent calculations, the units are matched and verified with the workload and number of days when the charging parameters are loaded. If inconsistencies in measurement methods are found, the units are converted and the results are recorded.

[0127] To ensure consistency in the units of measurement for all input quantities in revenue calculations, the system automatically performs unit matching and calibration verification when loading unit charging parameters. When a discrepancy is detected between the unit of measurement for charging parameters and the units used in input data such as workload and storage days, the system automatically invokes its built-in unit conversion module to perform a unified conversion. Specifically, the system automatically selects the corresponding conversion rule based on the physical attributes of the parameters: when the storage fee rate is based on "yuan / ton·day" and the workload is in "kilograms," the system converts the workload to tons according to the conversion relationship of 1 ton = 1000 kilograms; when the fee rate is based on "yuan / cubic meter × day" and the cargo volume is in "cubic feet," the system will automatically convert based on the conversion factor of 1 cubic meter ≈ 35.315 cubic feet; if some short-cycle operations are billed by "hour" but the model's base unit is "day," the system will perform a conversion of "1 day = 24 hours" to maintain consistency in the time scale. After the conversion is completed, the system automatically generates a unit conversion log, which records the parameter names, original values ​​and units, converted values ​​and units, conversion time and calculation coefficients involved in the conversion, in order to support subsequent traceability and verification.

[0128] During the revenue calculation process, the system calculates the annual revenue of each warehousing sub-unit based on the cargo volume statistics. The calculation formula is as follows:

[0129] ;

[0130] Calculate the annual revenue of the storage yard based on the storage yard's operational volume parameters. :

[0131] ;

[0132] in, This represents the unit storage fee rate for the nth type of storage sub-unit. This represents the unit storage fee rate corresponding to the storage yard. The above calculation is automatically completed by the system calling the revenue calculation program, and the input parameters and calculation results of each revenue item are recorded synchronously during the execution process.

[0133] In this embodiment, the annual revenue of each warehousing sub-unit is calculated based on the cargo volume statistics. Annual revenue of the storage yard The sum of these factors is used to comprehensively adjust the original returns. The system constructs a comprehensive influence factor A based on historical data, industry experience, and external information, and expresses it as A = x·f·r·p. A reflects the combined impact of multiple factors, such as project nature, risk level, financing costs, and operator preferences, on return forecasting. To ensure the feasibility and traceability of this factor's calculation, this embodiment further explains the basis for the values ​​of the four components, their numerical ranges, and the system's automated calculation method.

[0134] First, in determining the influencing factor x, the system preferentially employs expert knowledge and historical case benchmarking. The system automatically retrieves relevant evaluation factors based on characteristics such as project type, park location, policy orientation, and regional market saturation, using a pre-built expert rule base and industry database. For example, when the corresponding park is located near a deep-water port or free trade zone and belongs to strategic logistics types such as cold chain logistics, the system will calculate a relatively high project nature factor x based on the rule engine. The optimal value range for this factor is set between 0.8 and 1.3, reflecting the impact of the project's fundamental attributes on expected returns.

[0135] Secondly, in calculating the risk impact factor f, the system automatically extracts market risk, operational risk, policy risk, and natural risk indicators related to the plan from historical project databases and industry databases, and inputs them into a preset risk assessment model (such as a weighted scoring card model) for quantitative analysis. The risk score calculated by the model is then mapped to a numerical range of 0.9 to 1.1, thus forming the value of f, which reflects the degree of impact of uncertainties such as cargo volume fluctuations, equipment failures, and regulatory changes on revenue.

[0136] Secondly, the financing cost influencing factor *r* is obtained by the system directly calling the financial data interface to obtain the real-time Loan Prime Rate (LPR) or benchmark interest rate, and combined with financial parameters such as the operator's credit rating and financing structure (debt-to-equity ratio), the comprehensive financing cost is calculated through the built-in Weighted Average Cost of Capital (WACC) model. The system normalizes the calculated financing cost, mapping *r* to the range of 0.95 to 1.05 to reflect the degree to which different financing costs reduce net income.

[0137] Furthermore, the operator's historical preference identification factor p is automatically generated by the system using a pre-trained preference identification model (such as a regression model). Based on the operator's unique identifier (ID), the system retrieves the deviation between the predicted and actual returns of its historical projects and analyzes its preference characteristics for different investment types. After inputting historical data, the model can directly output the preference factor p, preferably with a value between 0.9 and 1.1, to reflect the prediction bias that may be caused by the operator's characteristics.

[0138] After calculating the four types of factors mentioned above, the system multiplies the values ​​of x, f, r, and p to obtain the comprehensive influence factor A, which is then used as the input parameter for the revenue calculation module. To ensure the transparency and traceability of subsequent calculations, the system will automatically record the values ​​of each component of A, the data source, and the generation time, and compare them with the unit storage fee rate of the storage sub-unit. Unit storage fee rate corresponding to the storage yard The source of the value is also stored in the log file.

[0139] The system then calculates the expected return by adjusting the individual annual revenues using factor A. :

[0140] ;

[0141] To ensure traceability of calculations, the source and collection time of the unit storage fee rate parameter corresponding to each planar unit are output synchronously during execution, and the components of the comprehensive influence factor A are also analyzed. Save the values ​​and descriptions for later review and recalculation.

[0142] The system invokes the built-in cost-benefit analysis program to automatically calculate the BCR value based on the following formula:

[0143] ;

[0144] After the calculation is completed, the system sorts the BCR values ​​of all schemes, preferably using quicksort or heapsort algorithms, and uses the sorting results as the basis for scheme selection, automatically selecting the scheme with the smallest BCR value from the sorting results as the preferred scheme.

[0145] Optionally, the system may also introduce a preset threshold. The plan is screened for eligibility: when When the m-th scheme meets the preset economic requirements, the schemes that meet the requirements are set as candidate schemes; if the candidate scheme set is not empty, further selection can be made from the candidate scheme set. The smallest solution is selected as the preferred solution; when the candidate solution set is empty, the system can output a prompt and allow adjustments. Then recalculate.

[0146] The system will ultimately output the total project investment corresponding to the optimal solution. Expected returns and each revenue item { , ,…, , The system retains the complete result set. It also preserves all intermediate parameters, unit conversion logs, factorization parameters, and calculation process records to support subsequent sensitivity analysis, result verification, and batch recalculation.

[0147] For scenarios requiring cross-year economic comparisons, the system accepts externally input discount rate parameters and can perform... and Discounting is performed separately to ensure that cost-benefit evaluation is conducted under a unified discounting standard, thereby maintaining consistency in evaluation across time dimensions.

[0148] Optionally, after calculating the cost-benefit ratio of multiple schemes, the key parameters of the selected optimal scheme (including the area ratio of each planar unit, the proportion of functional areas, and road dimensions, etc.) can be returned to the layout generation module in the form of structured data, so that the parameter set can be reused in subsequent scheme generation under the same constraints. This process does not involve automatic modification of the layout, but is used to achieve the inheritance of scheme parameters and cross-module data consistency, which facilitates designers to continue to carry out detailed design based on the optimal scheme.

[0149] Second preferred embodiment:

[0150] To further illustrate the specific implementation process of the port logistics park planning and design method described in the first preferred embodiment, this embodiment selects a set of specific parameters as example inputs under the given land boundary and functional requirements. A parametric planar model of the park is generated based on a parametric modeling program, and the corresponding area parameter dataset, cargo volume statistics, cost calculation results, and scheme evaluation results are output. The parameters described in this embodiment are merely examples used to illustrate the calculation and constraint setting process and do not constitute a limitation on the scope of protection of this invention.

[0151] Based on the site boundary and functional requirements, the geometric and associated parameter constraints of the planar elements in the Lingang Logistics Park plan model are determined as follows:

[0152] Since most warehouse buildings in logistics parks are single-story Class C warehouses, this embodiment uses a Class C warehouse as a sub-unit of the storage unit. According to fire safety regulations, the floor area of ​​a single-story Class C warehouse must not exceed 6000 m². 2 If the building is a logistics facility and meets the requirements for storing non-flammable liquids, textiles such as cotton, linen, silk, and wool, and foam plastics, this data can be relaxed to 24,000 m². 2 Therefore, the area of ​​a storage sub-unit should not exceed 24,000 m². 2 The depth of a single-sided process logistics building should not exceed 60m, and the depth of a double-sided process logistics building should not exceed 120m. Therefore, the width of a sub-unit should be less than 120m.

[0153] The storage unit includes a cold storage warehouse j1, a general cargo warehouse j2, and a dry bulk cargo warehouse j3; the geometric parameters of j1 are 70 m × 100 m, the geometric parameters of j2 are 80 m × 150 m, and the geometric parameters of j3 are 120 m × 200 m.

[0154] The yard unit follows the common container stacking method, with the geometric parameters of yard subunit d1 being 200 m × 100 m; the spacing between yard subunits is 10 m.

[0155] The road unit is divided into main roads, secondary roads, and fire lanes. The width of the main road L1 is set to 18m, the width of the secondary road L2 is set to 15m, and the width of the fire lane L3 is set to 4m.

[0156] The green space units are limited by the total logistics park area and the green space ratio, based on the planning indicator of green space ratio.

[0157] According to the "Logistics Building Design Code", the supporting units occupy 5%-10% of the total area W of the logistics park.

[0158] Other units Q1 refer to the parts within the logistics park excluding warehousing units, storage yard units, road units, supporting building units, and greening units.

[0159] Then, a parametric planar model of the Lingang Logistics Park was established using a parametric geometric modeling platform, and the associated parameters and parameter constraints of the parametric planar model were set, as shown in Table 2.

[0160] Table 2. Related Parameter Constraints

[0161]

[0162] Multiple parametric planar models of the port logistics park that meet the constraints are generated by calling a parametric modeling program, resulting in several planning and design schemes S1, S2, ..., S1 that meet the planning requirements and functional needs of the port logistics park. m There are a total of m sets, where m is a positive integer; the data in each planning and design scheme includes:

[0163] The number of each type of storage sub-unit is denoted as a. 1m a 2m ... a nm ;

[0164] Total area J of each type of storage sub-unit 1m J 2m ... J nm ;

[0165] The number of storage yard sub-units is denoted as b. 1m ;

[0166] Total area D of the storage yard sub-unit 1m ;

[0167] The length of the road sub-unit is denoted as c. 1m c 2m c 3m ;

[0168] Total area L of road sub-unit 1m L 2m L 3m ;

[0169] Supporting building unit P 1m ;

[0170] Green Unit G 1m ;

[0171] Other units Q 1m The value of Q 1m =WJ 1m -J 2m -J 3m -……-J nm -D 1m -L 1m -L 2m -……-L nm -P 1m -G 1m ,

[0172] Where W is the total land area of ​​the park, m represents the number of the m-th park planning and design scheme, and n represents the sequence number of different planar units within the scheme.

[0173] The following data uses S1 as an example:

[0174] The area of ​​the Lingang Logistics Park varies from a few hectares to several hundred hectares. We selected a logistics site on a certain planning map. The site area is 78.5 hectares, i.e., W = 785,000 m². 2 .

[0175] A certain scheme S1 is automatically generated by computer, wherein:

[0176] Number of cold storage units a 11 =6. Number of general merchandise warehouses a 21 =4. Number of dry bulk warehouses a 31 =4;

[0177] Cold storage area J 11 =7000×6=42000 m 2 J, area of ​​general merchandise warehouse 21 =12000×4=48000 m 2 Dry bulk warehouse area J 31 =24000×4=96000 m 2 ,

[0178] Number of storage yard sub-units: b 11 =12, Total area of ​​the storage yard sub-unit D 11 =240000 m 2 ;

[0179] Main road length c 11 =2314 m, length of secondary trunk road c 21 =4716.13, Fire branch length c 31 =1300 m;

[0180] Main road area L 11 =41652 m 2 Secondary arterial road area L 21 =70742 m 2 Fire branch area L 31 =5200 m 2 ,

[0181] The supporting facilities occupy an area of ​​P. 11 =60198m 2 ,

[0182] Calculate greening unit G 11 =49681m 2 ,

[0183] Calculate the area Q of other cells 11 =WJ 11 -J 21 -J 31 -D 11 -L 11 -L 21 -L 31 -P 11 -G 11 Q 11 =131527m 2 ;

[0184] The final output data for step S100 is shown in Table 3.

[0185] Table 3 Output Data Table for S100 Step

[0186]

[0187] Then, based on the actual area parameters of the Lingang Logistics Park planning and design scheme, the annual handling volume and average storage days of various types of goods are calculated.

[0188] For the nth type of storage sub-unit, its unit area storage capacity, area utilization rate, and storage days are set as follows in this embodiment:

[0189] First, determine the number of operating days for the logistics park per year. In this embodiment, =350.

[0190] For cold storage warehouses, the storage capacity per unit area is: The value of the amount of goods stored per unit area in the cold storage is shown in Table 4.

[0191] Table 4. Reference Range of Storage Capacity per Unit Area in Cold Storage

[0192]

[0193] In this embodiment, it is assumed to be frozen food, and the value is... =1.0 t / m 2 .

[0194] Cold storage area utilization rate The value can be between 0.6 and 0.7. In this embodiment, The value is 0.6.

[0195] Cold storage cargo storage volume: t;

[0196] The imbalance coefficient of goods storage in cold storage is: The value can range from 1.1 to 1.9. In this embodiment, The value is 1.5.

[0197] Average storage days in cold storage The average number of days for cold storage is determined based on actual cargo storage needs, as shown in Table 5.

[0198] Table 5. Average Storage Days in Cold Storage (Reference Table)

[0199]

[0200] In this embodiment, it is assumed that the meat is frozen pork, beef, or mutton. Values ​​are taken over 20 days.

[0201] Annual cargo handling volume of cold storage facilities: ;

[0202] For general merchandise warehouses, the storage capacity per unit area is: The value of the amount of goods stored per unit area in the general cargo warehouse is shown in Table 6.

[0203] Table 6 Reference Table for Inventory Quantity per Unit Area of ​​General Goods Warehouse

[0204]

[0205] In this embodiment, it is assumed to be steel. The value is 4.0 t / m 2 .

[0206] General warehouse area utilization rate The value can be between 0.6 and 0.7. In this embodiment, The value is 0.6.

[0207] General Goods Storage Quantity t;

[0208] The imbalance coefficient of goods storage in the general merchandise warehouse is: The value can range from 1.1 to 1.9. In this embodiment, The value is 1.5.

[0209] Average storage days in general merchandise warehouse The average storage days for general cargo warehouses are determined based on actual cargo storage needs, as shown in Table 7.

[0210] Table 7. Average Storage Days in the General Goods Warehouse (Reference Table)

[0211]

[0212] In this embodiment, it is assumed to be steel. Values ​​are taken over 60 days.

[0213] Annual cargo handling volume for general merchandise: ;

[0214] For dry bulk warehouses, the storage capacity per unit area is: The value of the amount of goods stored per unit area in the dry bulk warehouse is shown in Table 8.

[0215] Table 8 Reference Table for Cargo Storage Capacity per Unit Area in Dry Bulk Warehouses

[0216]

[0217] In this embodiment, coal is assumed to be used. The value is 2.5 t / m 2 .

[0218] Dry bulk warehouse area utilization rate The value can be between 0.6 and 0.7. In this embodiment, The value is 0.6.

[0219] Dry bulk cargo storage volume: t;

[0220] The imbalance coefficient of cargo storage in dry bulk warehouses is: The value can range from 1.1 to 1.9. In this embodiment, The value is 1.5.

[0221] Average storage days in dry bulk warehouses The actual storage requirements should be determined based on the actual needs of the goods, as shown in Table 9.

[0222] Table 9 Average Storage Days for Dry Bulk Cargo Warehouses

[0223]

[0224] In this embodiment, coal is assumed to be used. Values ​​are taken over 30 days.

[0225] Annual cargo handling volume of dry bulk warehouses:

[0226] ;

[0227] For containers, calculations are based on stacking layout and operational processes:

[0228] Based on the yard layout pattern, the container yard adopts a container reach stacker (or truck) operation method. This is combined with the yard layout dimension D given in this embodiment. 11 =200 m×100 m, which can be used to calculate the number of standard container rows and columns that can be arranged in the storage yard area.

[0229] This embodiment uses the following calculation method to determine the number of container slots in the storage yard:

[0230] In this embodiment, S1 includes 12 yard areas, each of which can accommodate 13 rows and 31 columns of containers;

[0231] Number of ground containers per yard unit: ;

[0232] Based on the container stacking process, this embodiment selects the number of stacking heights in the yard. ;

[0233] Yard area utilization rate The value is determined based on factors such as the layout of the storage yard aisles, the turning radius of equipment, and safety clearances, and is typically taken as 0.6 to 0.7. This embodiment selects... ;

[0234] Container yard cargo storage volume (Round up);

[0235] Inventory imbalance coefficient in storage yard The value is selected based on historical throughput fluctuations, typically ranging from 1.1 to 1.9. This embodiment selects... ;

[0236] Average storage days of containers The timeframe is determined based on actual operational needs, typically ranging from 5 to 10 days. In this example, it is set to: ;

[0237] Annual handling volume of the storage yard: (Round up);

[0238] According to the cost index database, the cost index per unit area is set separately according to the functional unit type. Units of the same type within the same scheme use the same cost index per unit area. The cost index per unit area for each planar unit is as follows:

[0239] The cost range for cold storage construction is 5500 yuan / m². 2~6500 yuan / m 2 The cost range for general cargo warehouses and dry bulk cargo warehouses is approximately 2000 yuan / m². 2 ~3000 yuan / m 2 In this embodiment, the preferred cost index for the cold storage unit is JZ1 = 6000 yuan / m². 2 The unit cost index for general merchandise warehouse JZ2 is 2500 yuan / m². 2 The unit cost index for dry bulk cargo warehouse JZ3 is 2500 yuan / m². 2 .

[0240] The value of the indicator affecting the cost of the stockyard is 300 yuan / m³. 2 ~500 yuan / m 2 In this embodiment, the cost index for the stockyard unit is DZ = 400 yuan / m². 2 .

[0241] The cost of road construction projects is mainly affected by the road grade; the cost range for main roads is 300 yuan / m. 2 ~500 yuan / m 2 The construction cost of secondary arterial roads and local roads is estimated at 300 yuan / m. 2 ~400 yuan / m 2 In this embodiment, the cost index for the main road unit is LZ1 = 400 yuan / m. 2 The cost index for secondary trunk road units, LZ2, is 350 yuan / m. 2 Branch road unit cost index LZ3 = 300 yuan / m 2 .

[0242] The supporting facilities are mostly auxiliary rooms, therefore the cost index for the supporting building unit is PZ = 3500 yuan / m². 2 ;

[0243] The quantity and type of trees and shrubs greatly influence the success of landscaping projects. In this example, general landscaping is sufficient, with a landscaping unit cost index of GZ = 100 yuan / m². 2 ;

[0244] Drainage and power supply are provided by external pipe networks. The cost index for the drainage unit is PSZ = 150 yuan / m. 2 The power supply unit cost index GDZ = 100 yuan / m 2 ;

[0245] In this embodiment, other units refer to paving works, and the cost index for other units is QZ = 400 yuan / m. 2 .

[0246] The construction cost of warehouse buildings (A1) is calculated according to the formula: "Construction cost of warehouse buildings = warehouse unit area × cost index per unit area of ​​warehouse".

[0247] The cost of the storage yard B1 is calculated as follows: "Storage yard cost = storage yard unit area × storage yard unit area index";

[0248] The road construction cost C1 is calculated according to the formula: "Road construction cost = Road unit area × Road unit area cost index";

[0249] The greening cost D1 is calculated according to the formula: "Greening cost = Greening unit area × Greening unit area cost index";

[0250] The cost of supporting building E1 is calculated as follows: "Cost of supporting building = Area of ​​supporting building unit × Cost index of supporting building unit area";

[0251] Other construction costs F1 are calculated as follows: "Other construction costs = area of ​​other units × cost index of other unit areas";

[0252] The drainage cost G1 is calculated according to the formula: "Drainage cost = Drainage unit area × Drainage unit area cost index".

[0253] The cost of power supply lighting H1 is calculated as follows: "Power supply lighting cost = power supply lighting unit area × power supply lighting unit area cost index".

[0254] By calculating the above costs, the total project cost of S1 can be obtained. =1079,252,400 yuan;

[0255] Other construction costs Where X is the comprehensive fee rate, which is 15%. Yuan;

[0256] Contingency Fund Yuan;

[0257] Total investment of the project Yuan;

[0258] According to market research data, the unit storage fee rate for goods corresponding to the nth type of storage subunit is:

[0259] Refrigerated goods K1 = 3 yuan / ton·day;

[0260] General cargo rate K2 = 0.8 yuan / ton / day;

[0261] Dry bulk freight rate K3 = 0.5 yuan / ton·day;

[0262] Container storage rate K d = 50 yuan / TEU·day.

[0263] Calculate the annual revenue for each storage sub-unit:

[0264] Refrigerated Goods RJ 11 =JL11 ×JT 11 ×K1=17,640,000 yuan;

[0265] RJ General Goods 21 =JL 21 ×JT 21 ×K2 = 21,500,000 yuan;

[0266] Dry bulk goods RJ 31 =JL 31 ×JT 31 ×K3 = 16,800,000 yuan;

[0267] Calculate the annual revenue of the storage yard unit: RD1 = DL 11 ×DT 11 ×K d =135,400,000 yuan;

[0268] The formula for calculating expected returns is:

[0269] ;

[0270] The comprehensive impact factor A = x·f·r·p, where x represents the project nature impact factor, f represents the risk situation impact factor, r represents the financing cost impact factor, and p represents the operator's historical preference identification factor;

[0271] After substituting, we obtain the expected return of scheme S1. =149,200,000 yuan / year.

[0272] Cost-benefit ratio is calculated using the following formula ;;

[0273] in The total investment of the project, For expected returns.

[0274] The cost-benefit ratio of scheme S1 was calculated. =8.73.

[0275] Calculate schemes S2 to S in the same way. m Given the BCR value, assuming that BCR1 has the smallest value, then S1 is selected as the preferred solution.

[0276] As can be seen from the above calculation process, the method of this invention can automatically complete layout generation, cargo volume and cost calculation, revenue analysis, and scheme comparison after inputting the basic parameters of the park. Compared with the traditional manual phased calculation method, this invention realizes the automated linkage between park planning and design and economic analysis, significantly improving the efficiency of scheme evaluation and the accuracy of decision-making.

[0277] Third preferred embodiment:

[0278] This invention provides a port logistics park planning and design system, comprising:

[0279] One or more processors;

[0280] Storage device for storing computer program instructions for executing the method described in the first preferred embodiment / second preferred embodiment;

[0281] When the one or more computer program instructions are executed by the one or more processors, the one or more processors perform the method as described in the first preferred embodiment / second preferred embodiment.

[0282] It also includes: a layout generation module, a cargo quantity calculation module, a cost calculation module, and a benefit analysis module.

[0283] The layout generation module is used to generate multiple sets of parametric planar models of the port logistics park that meet the constraints based on the set geometric parameter constraints and associated parameter constraints, and output m sets of park planning and design schemes and the corresponding unit parameter datasets for each scheme, where m is a positive integer.

[0284] Specifically, the unit parameter dataset includes: several planning and design schemes S1, S2, ..., S1 for the port logistics park that meet the planning requirements and functional needs. m There are a total of m sets, and the data in each planning and design scheme includes:

[0285] The number of each type of storage sub-unit is denoted as a. 1m a 2m ... a nm ; respectively corresponding to the first storage unit J1, the second storage unit J2, ..., the nth storage unit J n Quantity;

[0286] Total area J of each type of storage sub-unit 1m J 2m ... J nm ; respectively corresponding to the first storage unit J1, the second storage unit J2, ..., the nth storage unit J n The total area;

[0287] The number of storage yard sub-units is denoted as b. 1m ;

[0288] Total area D of the storage yard sub-unit 1m ;

[0289] The total length of each type of road sub-unit is denoted as c. 1m c 2m c 3mThese correspond to the total lengths of main roads, secondary roads, and fire lanes, respectively.

[0290] The total area of ​​each type of road sub-unit is denoted as L. 1m L 2m L 3m These correspond to the total area of ​​the main roads, secondary roads, and fire lanes, respectively.

[0291] Supporting building unit area P 1m ;

[0292] Green unit area G 1m ;

[0293] The area Q of other units 1m Q 1m =WJ 1m -J 2m -……-J nm -D 1m -L 1m -L 2m -L 3m -P 1m -G 1m ,

[0294] Where W is the total land area of ​​the park, m represents the number of the m-th park planning and design scheme, and n represents the sequence number of different planar units within the scheme.

[0295] The cargo volume calculation module is used to establish a quantitative mapping relationship from area parameters to storage volume and from storage volume to annual workload based on the unit parameter dataset, calculate the annual workload and average storage days of different types of goods, and output cargo volume statistics results.

[0296] The cost calculation module is used to calculate the itemized cost and engineering expenses of each planar unit based on the unit parameter dataset and the preset unit area cost index, and further calculate other construction costs and contingency funds, thereby obtaining and outputting the total investment of the project.

[0297] The benefit analysis module is used to calculate the sub-item revenue of the storage unit and the yard unit based on the cargo volume statistics, and to correct the sub-item revenue according to the comprehensive impact factor to obtain the expected revenue of each planning and design scheme; to calculate the cost-benefit ratio based on the total engineering investment and expected revenue of each scheme, and to determine the planning and design scheme with the smallest cost-benefit ratio from m planning and design schemes as the preferred scheme based on the cost-benefit ratio, and to output the preferred scheme and the corresponding total engineering investment, expected revenue and sub-item revenue results.

[0298] The area parameter data output by the layout generation module is used as input to the cargo quantity calculation module and the cost calculation module; the outputs of the cargo quantity calculation module and the cost calculation module are jointly input to the benefit analysis module, which evaluates multiple schemes and outputs the optimal result.

[0299] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented, in whole or in part, as a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0300] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A port logistics park planning and design method, characterized in that, The method comprises the following steps: According to the set geometric parameter constraints and associated parameter constraints, a parameterized modeling program is called to generate multiple sets of port logistics park parameterized plan models meeting the constraint conditions, and m sets of park planning and design schemes and unit parameter data sets corresponding to each scheme are output, wherein m is a positive integer; According to the unit parameter data set, a quantitative mapping relationship from the area parameter to the stock quantity and from the stock quantity to the annual operation quantity is established, the annual operation quantity and the average stock storage days of different types of goods are calculated, and the goods quantity statistical result is output; According to the unit parameter data set, the sub-item cost and engineering cost of each plan unit are calculated based on a preset unit area cost index, and further the other engineering construction costs and the reserve fund are calculated, so as to obtain the total engineering investment and output; According to the goods quantity statistical result, the sub-item income of the warehouse unit and the stock yard unit is calculated, and the sub-item income is corrected according to a comprehensive influence factor to obtain the expected income of each set of planning and design scheme; According to the total engineering investment and the expected income of each set of scheme, the cost-benefit ratio is calculated, the planning and design scheme with the minimum cost-benefit ratio is determined from the m sets of planning and design schemes as the preferred scheme, and the preferred scheme and the corresponding total engineering investment, expected income and sub-item income result are output.

2. The method according to claim 1, wherein: The plan unit includes a warehouse unit, a stock yard unit, a road unit, a supporting building unit, a green unit and other units.

3. The method of claim 1, wherein: The associated parameters include: land volume rate, building setback road distance, building setback land boundary distance, building setback wall distance, fireproof distance between buildings, fireproof distance between buildings and stock yard, supporting building unit area, green unit area and other unit area.

4. The method according to claim 1, wherein: The unit parameter data set corresponding to each planning and design scheme includes: the number and total area of each type of warehouse sub-unit, the number and total area of stock yard sub-unit, the total length and total area of each type of road sub-unit, the area of supporting building unit, the area of green unit and the area of other unit.

5. The method of claim 1, wherein: The calculation of the annual operation quantity is based on the unit area stock quantity, the area utilization rate, the unbalanced coefficient and the average stock storage days, and the quantitative mapping relationship is established between the area parameter and the stock quantity.

6. The method of planning and designing a port logistics park according to claim 1, wherein: The sub-item income includes the annual income obtained according to the operation quantity, the average stock storage days of the warehouse unit and / or the stock yard unit and the corresponding unit charging parameter.

7. The method of claim 1, wherein: The comprehensive influence factor is represented as A=x·f·r·p, wherein x represents the project property influence factor, f represents the risk situation influence factor, r represents the financing cost influence factor, and p represents the operation party historical preference identification factor.

8. A port logistics park planning and design system, characterized in that, The method comprises the following steps: One or more processors; A storage device for storing computer program instructions for executing the method of any one of claims 1-7; When the one or more computer program instructions are executed by the one or more processors, the one or more processors implement the method of any one of claims 1-7, Further comprising: a layout generation module, a goods quantity calculation module, a cost calculation module and a benefit analysis module, The layout generation module is configured to call a parameterized modeling program to generate multiple sets of parameterized park planning design schemes that satisfy the constraint conditions according to the set geometric parameter constraints and the associated parameter constraints, and output m sets of park planning design schemes and unit parameter data sets corresponding to each scheme, where m is a positive integer. The cargo volume calculation module is configured to establish quantitative mapping relationships from area parameters to storage volumes and from storage volumes to annual handling volumes according to the unit parameter data sets, calculate annual handling volumes and average storage days of different types of cargos, and output cargo volume statistical results. The cost calculation module is configured to calculate sub-item costs and engineering costs of each plane unit based on a preset unit area cost index according to the unit parameter data sets, further calculate other engineering construction costs and reserve costs, and thus obtain total project investment and output. The benefit analysis module is configured to calculate sub-item benefits of warehouse units and yard units according to the cargo volume statistical results, correct the sub-item benefits according to comprehensive influence factors to obtain expected benefits of each set of planning design schemes, calculate cost-benefit ratios according to total project investment and expected benefits of each set of scheme, determine a planning design scheme with the minimum cost-benefit ratio from the m sets of planning design schemes as an optimal scheme according to the cost-benefit ratios, and output the optimal scheme and corresponding total project investment, expected benefits, and sub-item benefit results.

9. A computer-readable storage medium storing a computer program, characterized in that, The program is executed by the processor to implement the method of any one of claims 1-7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1-7.

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