Logistics path determination method and apparatus, and electronic device

Abstract

The invention discloses a logistics path determination method, which comprises the following steps: acquiring a plurality of logistics paths of a building object, extracting dimension parameters of a plurality of target dimensions in the logistics paths, determining a total evaluation value of each logistics path according to a weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension, and determining a logistics path based on the total evaluation value. According to the method, the target logistics path is determined from all the logistics paths, so that the optimal logistics path can be determined as the target logistics path based on the evaluation values of different dimensions, the dependence on professionals is reduced, the accuracy of determining the logistics path is improved, and the user experience is improved. And the number of times of modifying the target logistics path is smaller than the number of times of modifying other logistics paths, so that the efficiency of determining the logistics path is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, and electronic device for determining logistics routes. Background Technology

[0002] With the development of building technology, buildings are becoming larger and larger, and are equipped with more and more functions. As a result, the types and quantities of materials, equipment and other resources required to meet each function are also increasing, making the method of transporting resources manually inefficient.

[0003] For example, as hospitals grow larger, they have more and more departments, examination rooms, and functional rooms. Different departments require different supplies and equipment. Currently, preparing the corresponding quantity and type of supplies and equipment for different departments, examination rooms, and functional rooms relies on manual transportation of supplies, which is inefficient.

[0004] Currently, the efficiency of transportation resources can be improved by installing a logistics system and utilizing the transportation equipment within the system to transport the resources needed for construction.

[0005] However, the design of routes in logistics systems relies on the experience of professionals, which leads to low accuracy. Professionals need to repeatedly modify the designed routes, resulting in low efficiency in the design of logistics systems. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, apparatus and electronic device for determining logistics routes.

[0007] In a first aspect, embodiments of the present invention provide a method for determining a logistics route, the method comprising: A method for determining a logistics route, characterized in that the method includes: Obtain multiple logistics paths for a building object, and extract dimensional parameters for multiple target dimensions from the logistics paths; The total evaluation value of each logistics path is determined based on the weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension. Based on the overall evaluation value, the target logistics path is determined from all the logistics paths.

[0008] In one possible implementation of the first aspect described above, the method further includes: Based on the dimension parameters, determine the target dimension parameters for each target dimension; Determine the difference between the dimensional parameter and the target dimensional parameter in each of the logistics paths; The process of determining the target logistics path from all the logistics paths based on the overall evaluation value includes: Based on the total evaluation value and the difference value, the target logistics path is determined from all the logistics paths.

[0009] In one possible implementation of the first aspect above, the target dimension parameters include positive target dimension parameters and negative target dimension parameters, and determining the target dimension parameter for each target dimension based on the dimension parameters includes: A standardized matrix is ​​generated based on the dimension parameters; wherein the standardized matrix includes the standardized value of each dimension parameter; The standardized matrix is ​​weighted according to the weight coefficients corresponding to the target dimensions to obtain the positive target dimension parameters and negative target dimension parameters for each target dimension.

[0010] In one possible implementation of the first aspect above, the difference value includes positive difference values ​​and negative difference values, and determining the target logistics path from all the logistics paths based on the total evaluation value and the difference value includes: Based on the positive and negative difference values, determine the relative difference value for each logistics path; The relative difference value and the total evaluation value are weighted according to preset weights to obtain the relative evaluation value of each logistics path; The logistics path with the highest relative evaluation value is determined as the target logistics path.

[0011] In one possible implementation of the first aspect above, determining the total evaluation value of each logistics path based on the weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension includes: Based on the dimension parameters, determine the objective weight coefficient for each target dimension; Based on the objective weight coefficient and the preset subjective weight coefficient, the target weight coefficient corresponding to the target dimension is determined; wherein, the subjective weight coefficient is determined based on the relative weight between each target dimension, and the relative weight is determined based on subjective factors; Based on the dimension parameters of each target dimension, the comparison weight between each logistics path is determined; wherein, the comparison weight includes the comparison weight corresponding to each target dimension; The total evaluation value for each logistics route is determined based on the target weight coefficient and the comparison weight.

[0012] In one possible implementation of the first aspect above, before determining the target weight coefficient corresponding to the target dimension based on the objective weight coefficient and the preset subjective weight coefficient, the method further includes: Obtain the scale value set for each of the target dimensions; Based on the scale value, determine the undetermined weights for each of the target dimensions, and determine the consistency index of the judgment matrix based on the undetermined weights; When the consistency index is less than the preset index threshold, the undetermined weight is determined to be a subjective weight coefficient. When the consistency index is greater than or equal to the index threshold, the scaling value is adjusted until the consistency index is less than the index threshold.

[0013] In one possible implementation of the first aspect above, determining the objective weight coefficient for each target dimension based on the dimension parameter includes: Determine the standardized value of each of the dimension parameters, and determine the entropy value of each of the target dimensions based on the standardized values; Based on the entropy value of each target dimension, determine the objective weight coefficient of each target dimension.

[0014] Secondly, embodiments of the present invention provide a device for determining a logistics path, the device comprising: The acquisition module is used to acquire multiple logistics paths for building objects; The extraction module is used to extract dimensional parameters of multiple target dimensions in the logistics path; The evaluation module is used to determine the total evaluation value of each logistics path based on the weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension. A determination module is used to determine a target logistics path from all the logistics paths based on the total evaluation value.

[0015] Thirdly, embodiments of the present invention provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the logistics path as described above.

[0016] Fourthly, embodiments of the present invention provide a computer program product, the computer program product storing a computer program, which, when executed by a processor, implements the method for determining the logistics path as described above.

[0017] This invention is achieved through the following technical solution: This invention discloses a method for determining logistics routes. By acquiring multiple logistics routes of a building object and extracting dimensional parameters of multiple target dimensions from the logistics routes, a total evaluation value for each logistics route is determined based on the weight coefficients corresponding to each target dimension and the dimensional parameters of each target dimension. Based on the total evaluation value, a target logistics route is determined from all logistics routes. This method can determine the optimal logistics route as the target logistics route based on the evaluation values ​​of different dimensions, reducing reliance on professional personnel, improving the accuracy of logistics route determination, and reducing the number of modifications to the target logistics route compared to other logistics routes, thus improving the efficiency of logistics route determination. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the steps of a method for determining a logistics route according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a decision matrix provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a standardized matrix provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a weighted and standardized matrix provided in an embodiment of the present invention; Figure 5 This is a flowchart of another method for determining a logistics route provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a judgment matrix provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of a logistics path determination device provided in an embodiment of the present invention; Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0020] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to that other component.

[0021] It should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention.

[0022] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, "a plurality of sets" means two or more sets, "a plurality of pieces" means two or more pieces, and "a number" means one or more, unless otherwise explicitly specified.

[0023] With the development of building technology, buildings are becoming larger and larger, and are equipped with more and more functions. As a result, the types and quantities of materials, equipment and other resources required to meet each function are also increasing, making the method of transporting resources manually inefficient.

[0024] For example, as hospitals grow larger, they have more and more departments, examination rooms, and functional rooms. Different departments require different supplies and equipment. Currently, preparing the corresponding quantity and type of supplies and equipment for different departments, examination rooms, and functional rooms relies on manual transportation of supplies, which is inefficient.

[0025] Currently, the efficiency of transportation resources can be improved by adding logistics systems, such as rail systems, box-type logistics systems, and pneumatic pipeline systems, and utilizing the transportation equipment in these systems to transport the resources needed for construction.

[0026] However, the installation of a logistics system typically involves the design of logistics routes. These routes rely heavily on the experience of professionals, leading to potential issues with accuracy. Furthermore, different professionals may design different routes. Since logistics routes can interfere with the building's mechanical and electrical (MEM) systems, HVAC systems, plumbing structures, and overall building structure, modifications to these systems are often necessary. For structures or systems that cannot be modified, adjustments to the logistics route are required, necessitating repeated revisions and resulting in low efficiency. Moreover, different professionals require different modifications to their chosen routes. Determining the optimal logistics route from multiple designs also relies on the experience of the professionals, again leading to potential issues with the accuracy of the selected route.

[0027] In summary, because the design of logistics routes relies on the experience of professionals, and the selection of the optimal logistics route from different options also depends on the experience of professionals, there is a problem of low accuracy in the design of logistics routes.

[0028] Based on this, the present invention discloses a method for determining logistics routes. By acquiring multiple logistics routes of a building object and extracting dimensional parameters of multiple target dimensions from the logistics routes, the total evaluation value of each logistics route is determined according to the weight coefficient corresponding to each target dimension and the dimensional parameters of each target dimension. Based on the total evaluation value, the target logistics route is determined from all logistics routes. This enables the determination of the optimal logistics route as the target logistics route based on the evaluation values ​​of different dimensions, reduces the reliance on professional personnel, improves the accuracy of determining logistics routes, and increases the efficiency of determining logistics routes by modifying the target logistics route less than modifying other logistics routes.

[0029] See Figure 1 , Figure 1 The diagram illustrates a flowchart of a method for determining a logistics route according to an embodiment of the present invention, which may specifically include the following steps: S101, obtain multiple logistics paths of the building object, and extract the dimension parameters of multiple target dimensions in the logistics paths.

[0030] The building object can be any building requiring a logistics system, such as a hospital or production workshop. The logistics system can be a system that transports materials to their required locations using transport equipment. The logistics path can be the path along which the logistics system transports materials within the building object, specifically including the path from any material storage location to the required location. The target dimension can be any dimension related to the construction of the logistics path among multiple dimensions describing the logistics path. Dimensions describing the logistics path can include the starting point, ending point, identifier, length, installation height, and location of the logistics path. The target dimension can include the net height of the logistics path installed on different floors, the cost related to the structural alteration of the building object when installing the logistics path, the efficiency of the logistics path in transporting materials, and the number of areas where the logistics path interferes with the building object's structure. Dimension parameters can describe the result of the logistics path in a specific dimension, such as a logistics path length of 100 meters, meaning the logistics path's measurement result in the length dimension is 100 meters, or the logistics path identifier being logistics path A, meaning the logistics path's result in the identifier dimension is logistics path A.

[0031] When a logistics system needs to be installed on any building object, the building information of the building object can be obtained.

[0032] Specifically, building information for any building object can be obtained from the Building Information Modeling (BIM) platform. This building information includes information about the building object in various models such as 3D models, plumbing models, and HVAC models.

[0033] In practical applications, the building object can be a hospital building. A BIM model of the hospital building can be built based on the design drawings of the hospital building. Then, when it is necessary to add a logistics system to the hospital building, the building information of the hospital building can be obtained from the BIM model of the hospital building, specifically including the information of the hospital building in terms of 3D model, water supply and drainage model, HVAC model, etc.

[0034] After obtaining the building information, the areas where materials are stored and the areas where materials need to be transported can be determined from the building information. Then, multiple logistics paths can be generated based on the three-dimensional coordinates of the areas where materials are stored and the three-dimensional coordinates of the areas where materials need to be transported. In other words, multiple logistics paths are generated between the areas where materials are stored and the areas where materials need to be transported, thus obtaining multiple logistics paths in the building object.

[0035] For example, a hospital building may have a multi-story structure with multiple different departments on different floors. Different departments require different medical supplies and have different electromechanical pipeline layouts. Therefore, it is necessary to determine the medical supplies required by each department and the area in the hospital building where the supplies are stored. Based on the three-dimensional coordinates of the storage area and the three-dimensional coordinates of each department, multiple logistics paths are generated to obtain multiple logistics paths in the hospital building.

[0036] In practical applications, logistics routes can be generated by multiple professionals based on the three-dimensional coordinates of the area where the goods are stored, the three-dimensional coordinates of the area where the goods need to be transported, and the three-dimensional model of the building object.

[0037] After obtaining multiple logistics paths, we can extract dimensional parameters of multiple target dimensions in the logistics paths, such as dimensional parameters of net height, cost, efficiency, and number of interferences for each logistics path.

[0038] In practical implementation, since the building object can be a multi-story structure, logistics routes can be installed on different floors of the building object, and the net height of the logistics routes on different floors can also be different. Based on this, for each logistics route, the net height of the logistics route on each floor can be scored, and the average score of the logistics route can be determined based on the score of the logistics route on each floor, which is the dimensional parameter of the logistics route in the net height dimension.

[0039] For example, for basement floors, a score of 10 is given when the clear height is 2.6 meters or higher, 8 points when it is 2.4 meters or higher but lower than 2.6 meters, and 6 points when it is lower than 2.4 meters. For above-ground floors, a score of 10 is given when the clear height is 2.8 meters or higher, 8 points when it is 2.8 meters or higher but lower than 2.6 meters, and 6 points when it is lower than 2.6 meters. Logistics route A has a clear height of 2.2 meters on the basement floor, 2.8 meters on the first floor, and 2.7 meters on the second floor. Therefore, logistics route A scores 6 points on the basement floor, 10 points on the first floor, and 8 points on the second floor, resulting in an average score of 8 points, which is the dimensional parameter of logistics route A in the clear height dimension.

[0040] S102, determine the total evaluation value of each logistics path based on the weight coefficients corresponding to each target dimension and the dimension parameters of each target dimension.

[0041] Among them, the weight coefficient can be the weight of the target dimension when evaluating the logistics path, and the total evaluation value can be the evaluation of the logistics path among all the logistics paths obtained.

[0042] After obtaining the dimensional parameters of each target dimension, the weight coefficient corresponding to each target dimension can be determined in advance. Then, for each logistics path, the total evaluation value of the logistics path can be determined based on the weight coefficient corresponding to each target dimension and the dimensional parameters of each target dimension in the logistics path. Thus, the total evaluation value of each logistics path can be obtained.

[0043] Specifically, the weight coefficients for each target dimension can be determined by the user based on experience, and the total evaluation value can be obtained by weighting the dimension parameters of each target dimension according to the weight coefficients for each target dimension.

[0044] In practical applications, when multiple logistics routes are available, the design of these routes relies heavily on the experience of professionals, and consequently, determining the optimal route from among them also depends on that experience, leading to a low accuracy rate in route design. Therefore, this paper addresses this issue by extracting dimensional parameters of the logistics routes across different dimensions. Each logistics route is evaluated based on these dimensional parameters, enabling the evaluation of routes using quantifiable, objective parameters. This reduces reliance on professional judgment, minimizing the subjective influence of professionals and improving the accuracy of determining the optimal logistics route from multiple options.

[0045] S103, Based on the overall evaluation value, determine the target logistics route from all logistics routes.

[0046] The target logistics path can be the optimal logistics path among all generated logistics paths, that is, the optimal logistics path in the target dimension.

[0047] After obtaining the total evaluation value for each logistics route, the logistics route with the highest total evaluation value can be determined as the target logistics route.

[0048] In one embodiment of the present invention, the method may further include the following steps: Based on the dimension parameters, determine the target dimension parameters for each target dimension, and determine the difference between the dimension parameters and the target dimension parameters in each logistics path.

[0049] The target dimension parameter can be the ideal solution among all dimension parameters. The ideal solution can be a parameter determined based on all dimension parameters. Target dimension parameters can include positive and negative target dimension parameters. A positive target dimension parameter can be a positive ideal solution, i.e., the optimal parameter determined based on all dimension parameters. A negative target dimension parameter can be a negative ideal solution, i.e., the worst parameter determined based on all dimension parameters. The difference value can be represented as the difference between the target dimension parameter and the target dimension parameter. Difference values ​​can include positive and negative difference values. A positive difference value can be the difference between the dimension parameter and the positive target dimension parameter, and a negative difference value can be the difference between the dimension parameter and the negative target dimension parameter.

[0050] After obtaining the total evaluation value for each logistics route, the target dimension parameter for each target dimension can be determined based on the dimension parameters of all target dimensions in each logistics route, and the difference between the dimension parameters in each logistics route and the target dimension parameter can be determined.

[0051] In one embodiment of the present invention, the target dimension parameters for each target dimension can be determined in the following manner: Based on the dimension parameters, a standardized matrix is ​​generated. The standardized matrix is ​​then weighted according to the weight coefficients corresponding to the target dimensions to obtain the positive and negative target dimension parameters for each target dimension.

[0052] The standardized matrix can include the standardized value of each dimension parameter, which can be the value obtained after standardizing the dimension parameter.

[0053] After obtaining the dimensional parameters of each logistics path, a decision matrix can be constructed based on the dimensional parameters of all target dimensions in each logistics path.

[0054] For example, see Figure 2 , Figure 2 The diagram illustrates a decision matrix according to an embodiment of the present invention, as shown below. Figure 2 As shown, the decision matrix can include the dimensional parameters of each logistics path, and each column of data represents the dimensional parameters of each logistics path in different dimensions. Each row of data can represent the dimensional parameters of each path in the corresponding target dimension. For example, the data in the first column can represent the data of the first logistics path, the data in the second column can represent the data of the second logistics path, and so on. The data in the first row can represent the dimensional parameters of each logistics path in the net height dimension, and the data in the second row can represent the dimensional parameters of each logistics path in the cost dimension.

[0055] After obtaining the decision matrix, vector normalization can be used to standardize all the data in the decision matrix to obtain a standardized matrix.

[0056] Specifically, the square root of the sum of squares of the data in each row of the decision matrix can be calculated, and the dimensional parameters of each row can be normalized based on the obtained square root results to obtain the standardized value of each dimensional parameter, that is, the standardized matrix including the standardized value of each dimensional parameter.

[0057] Refer to the following formula, which can be used to calculate the square root of the sum of squares of each row of data in the decision matrix: First line C1:

[0058] Second line C2:

[0059] Third line C3:

[0060] Fourth line C4:

[0061] After obtaining the square root result of each row of data, the corresponding row of data in the decision matrix can be normalized based on the square root result of each row to obtain a standardized matrix.

[0062] Refer to the following formula, which can be used for normalization: First line C1: C1 = 8.0 / 13.983 ≈ 0.572 Second line C2: C2 = 113.5 / 202.866 ≈ 0.559 Third line C3: C3 = 1858.13 / 2953.091 ≈ 0.629 Fourth line, C4: C4 = 269 / 499.986 ≈ 0.538 It is important to understand that the above calculation example only normalizes the data in the first column of the decision matrix. The data in the remaining columns of the decision matrix can be normalized in the same way as the example above to obtain a standardized matrix.

[0063] See Figure 3 , Figure 3 A schematic diagram of a standardized matrix provided in an embodiment of the present invention is shown, as follows. Figure 3 As shown, the standardized matrix can include data obtained by normalizing the dimensional parameters of each logistics path.

[0064] After obtaining the standardized matrix, the data in the standardized matrix can be weighted according to the weight coefficients corresponding to each target dimension to obtain the weighted standardized matrix. This is done by multiplying the weight coefficients corresponding to the data in each column of the standardized matrix to obtain the weighted data for each column.

[0065] For example, the weight coefficient corresponding to each target dimension can be: W = [0.4125, 0.2548, 0.1496, 0.1838] The first column of data can be represented as the weight coefficient for the net height dimension, the second column as the weight coefficient for the cost dimension, the third column as the weight coefficient for the efficiency dimension, and the fourth column as the weight coefficient for the number of interventions dimension.

[0066] See the formula below; each column of data can be weighted using the following formula: First column: [0.572×0.4125,0.559×0.2548,0.629×0.1496,0.538×0.1838] =[0.236, 0.142, 0.094, 0.099] Second column: [0.477×0.4125,0.486×0.2548,0.503×0.1496,0.448×0.1838] =[0.197, 0.124, 0.075, 0.082] The third column: [0.667×0.4125, 0.671×0.2548, 0.592×0.1496, 0.714×0.1838] = [0.275, 0.171, 0.089, 0.131] It is important to understand that the above calculation example only performs weighted operations on the data in the first to third columns of the decision matrix. The data in the remaining columns of the decision matrix can be weighted in the same way as the above example to obtain the weighted data for each column.

[0067] See Figure 4 , Figure 4 This diagram illustrates a weighted, standardized matrix according to an embodiment of the present invention, as shown below. Figure 4 As shown, the standardized matrix after weighted operation can include the data obtained after weighted operation on the standardized matrix.

[0068] After obtaining the weighted and standardized matrix, the optimal and worst parameters for each objective dimension can be determined based on the data in the weighted and standardized matrix.

[0069] In practical applications, the evaluation type for each target dimension can be determined, that is, the relationship between the dimensional parameters of the target dimension and the evaluation logistics path.

[0070] Specifically, for the net height and efficiency dimensions, the evaluation type is positively correlated, that is, the larger the value of the dimension parameter of the net height or efficiency dimension, the higher the evaluation of the logistics path. For the cost and interference quantity dimensions, the evaluation type is negatively correlated, that is, the smaller the value of the dimension parameter of the cost or interference quantity dimension, the higher the evaluation of the logistics path.

[0071] After determining the evaluation type for each target dimension, the optimal and worst parameters of the target dimension can be determined from the weighted standardized matrix based on the evaluation type of the target dimension, thus obtaining the positive and negative target dimension parameters for each target dimension.

[0072] For example, since the first row of data in the weighted standardized matrix is ​​the dimension parameter of the net height dimension, and the evaluation type of the net height dimension is positive correlation, the dimension parameter with the largest value can be determined from all the first row of data in the weighted standardized matrix as the optimal parameter of the net height dimension in all logistics paths, and the dimension parameter with the smallest value can be determined from all the first row of data in the weighted standardized matrix as the worst parameter of the net height dimension in all logistics paths. Similarly, the optimal and worst parameters of the efficiency dimension can be determined from the third row of data.

[0073] The second row of data in the weighted standardized matrix represents the dimension parameters of the cost dimension, and the evaluation type of the cost dimension is negative correlation. Therefore, the dimension parameter with the smallest value can be determined from all the second row data of the weighted standardized matrix as the optimal parameter of the cost dimension in all logistics paths, and the dimension parameter with the largest value can be determined from all the first row data of the weighted standardized matrix as the worst parameter of the cost dimension in all logistics paths. Similarly, the optimal and worst parameters of the interference quantity dimension can be determined from the fourth row data.

[0074] As an example, after obtaining the positive and negative target dimension parameters for each target dimension, the positive and negative difference values ​​for each logistics path can be determined based on the positive and negative target dimension parameters.

[0075] Specifically, the positive variance value for each logistics route can be determined using the following formula:

[0076] in, It can be the positive difference value for the i-th logistics path. It can be the positive target dimension parameter of the j-th target dimension. It can be the dimension parameter of the j-th target dimension in the i-th logistics path, and n can be the total number of target dimensions in the i-th logistics path.

[0077] Specifically, the negative variance value for each logistics route can be determined using the following formula:

[0078] in, It can be the negative difference value of the i-th logistics path. It can be the negative target dimension parameter of the j-th target dimension. It can be the dimension parameter of the j-th target dimension in the i-th logistics path, and n can be the total number of target dimensions in the i-th logistics path.

[0079] In one embodiment of the present invention, S103 may include the following steps: Based on the overall evaluation value and the difference value, the target logistics route is determined from all logistics routes.

[0080] After obtaining the total evaluation value and the difference value, the target logistics path can be determined from all logistics paths based on the total evaluation value and the difference value of each logistics path.

[0081] In practical applications, the logistics path with the highest total evaluation value and the largest difference value can be identified as the target logistics path from each logistics path. Alternatively, the sum of the total evaluation value and the difference value in each logistics path can be calculated, and the logistics path with the largest sum can be identified as the target logistics path.

[0082] In one embodiment of the present invention, the target logistics route can also be determined in the following manner: Based on the positive and negative difference values, the relative difference value of each logistics path is determined. The relative difference value and the total evaluation value are weighted according to the preset weights to obtain the relative evaluation value of each logistics path. The logistics path with the largest relative evaluation value is determined as the target logistics path.

[0083] Among them, the relative difference value can represent the difference between the dimension parameter of the target dimension and the dimension parameter of the positive target dimension in the logistics path, and the relative evaluation value can be the value for evaluating the logistics path based on the total evaluation value and the relative difference value.

[0084] After obtaining the positive and negative difference values, the relative difference value for each logistics route can be determined based on these values.

[0085] Specifically, the relative difference value can be determined using the following formula:

[0086] in, This can be the relative difference value for the i-th logistics path. It can be the negative difference value of the i-th logistics path. It can be the positive difference value of the i-th logistics path.

[0087] After obtaining the relative difference value of each logistics path, the relative difference value and the total evaluation value can be weighted according to the preset weights to obtain the relative evaluation value of each logistics path, and the logistics path with the largest relative evaluation value is determined as the target logistics path.

[0088] Specifically, the preset weights can be user-defined or determined based on experience. For example, the weight of the total evaluation value can be set to 0.8, and the weight of the relative difference value can be set to 0.2.

[0089] In this embodiment of the invention, multiple logistics paths of a building object are obtained, and the dimension parameters of multiple target dimensions in the logistics paths are extracted. Based on the weight coefficients corresponding to each target dimension and the dimension parameters of each target dimension, the total evaluation value of each logistics path is determined. Based on the total evaluation value, the target logistics path is determined from all logistics paths. This enables the determination of the optimal logistics path as the target logistics path based on the evaluation values ​​of different dimensions, reduces the reliance on professional personnel, improves the accuracy of determining logistics paths, and increases the efficiency of determining logistics paths by modifying the target logistics path less than modifying other logistics paths.

[0090] See Figure 5 , Figure 5 The present invention illustrates a flowchart of another method for determining a logistics route according to an embodiment of the present invention, which may specifically include the following steps: S501, obtain multiple logistics paths of the building object, and extract the dimension parameters of multiple target dimensions in the logistics paths.

[0091] S502, based on the dimension parameters, determine the objective weight coefficient for each target dimension.

[0092] Among them, the objective weight coefficient can be a weight determined based on the dispersion of the dimension parameter of the target dimension, so as to determine the impact of the target dimension on the evaluation of the logistics path from the perspective of the dispersion of the data.

[0093] After obtaining the dimension parameters of each target dimension, the entropy value of each target dimension can be calculated based on the dimension parameters of each target dimension, thus obtaining the objective weight coefficient of each target dimension.

[0094] In one embodiment of the present invention, S502 may include S5021 to S5022: S5021, determine the standardized value of each dimension parameter, and determine the entropy value of each target dimension based on the standardized value.

[0095] The standardized value can be the value obtained after standardizing the dimensional parameter, and the entropy value can be represented as the degree of dispersion of the dimensional parameter.

[0096] After obtaining the dimensional parameters of each target dimension, the dimensional parameters of each target dimension can be standardized to obtain the standardized value of each dimensional parameter.

[0097] In practical applications, dimensionless processing can also be used to standardize dimensional parameters. Specifically, for dimensional parameters with a positive correlation evaluation type, the following formula can be used for dimensionless processing:

[0098] in, It can be the dimensionless result of the j-th target dimension in the i-th logistics path. It can be the dimension parameter of the j-th target dimension in the i-th logistics path. It can be the minimum value among all dimensional parameters of the j-th target dimension. It can be the maximum value among all dimensional parameters of the j-th target dimension.

[0099] For dimension parameters whose evaluation type is negative correlation, the following formula can be used for dimensionless processing:

[0100] in, It can be the dimensionless result of the j-th target dimension in the i-th logistics path. It can be the dimension parameter of the j-th target dimension in the i-th logistics path. It can be the minimum value among all dimensional parameters of the j-th target dimension. It can be the maximum value among all dimensional parameters of the j-th target dimension.

[0101] After obtaining the standardized values ​​of each dimension parameter, for each target dimension, the standardized values ​​of the dimension parameters in that target dimension can be normalized to obtain the proportion of each logistics path under different target dimensions.

[0102] Specifically, for each logistics route, the sum of all standardized values ​​in any target dimension can be calculated, and the ratio between the standardized value of the logistics route in that target dimension and the sum can be determined. This is the result of normalizing the standardized values ​​of the target dimension in the logistics route, thus obtaining the normalized result of each standardized value, which is the proportion of each logistics route under different target dimensions.

[0103] For example, the standardized value of logistics path A in the net height dimension can be 0.5, the standardized value of logistics path B in the net height dimension can be 0, and the standardized value of logistics path C in the net height dimension can be 1. Then the sum of all standardized values ​​in the net height dimension can be calculated to be 1.5. Therefore, the ratio between the standardized value of logistics path A in the net height dimension and the sum of all standardized values ​​can be determined to be 0.5 / 1 = 0.333. Similarly, the ratio of logistics path B in the net height dimension can be obtained as 0, and the ratio of logistics path C in the net height dimension is 0.667.

[0104] After obtaining the proportion of each logistics route under different target dimensions, the entropy value of each target dimension can be determined using the following formula:

[0105] in, Let m be the entropy value of the j-th target dimension, and m be the total number of logistics paths. This can be the proportion of the i-th logistics route in the j-th target dimension.

[0106] S5022, determine the objective weight coefficient for each target dimension based on the entropy value of each target dimension.

[0107] After obtaining the entropy value of each target dimension, the objective weight coefficient of each target dimension can be determined based on the entropy value of each target dimension.

[0108] Specifically, the objective weighting coefficient can be determined using the following formula:

[0109] in, This can be the objective weight coefficient for the j-th target dimension. It can be the entropy value of the j-th target dimension, and n can be the total number of all target dimensions.

[0110] S503, determine the target weight coefficient corresponding to the target dimension based on the objective weight coefficient and the preset subjective weight coefficient.

[0111] The subjective weight coefficients can be determined based on the relative weights between each target dimension, and these relative weights can be determined based on subjective factors. The target weight coefficients can be the final weights used to evaluate the logistics route.

[0112] After obtaining the objective weighting coefficients, the pre-set subjective weighting coefficients can be determined.

[0113] Specifically, the subjective weight coefficient can be determined based on the relative weight between each target dimension, and the relative weight can be determined based on subjective factors, specifically values ​​set by the user or values ​​determined based on experience.

[0114] In one embodiment of the present invention, before S503, the following steps may be included: Obtain the scale value set for each target dimension, determine the undetermined weight for each target dimension based on the scale value, and determine the consistency index of the judgment matrix based on the undetermined weight. When the consistency index is less than the preset index threshold, determine the undetermined weight as the subjective weight coefficient. When the consistency index is greater than or equal to the index threshold, adjust the scale value until the consistency index is less than the index threshold.

[0115] The calibration values ​​can be the values ​​that indicate the importance of the target dimensions, representing the importance of each target dimension in evaluating the logistics path in numerical form. Specifically, this can include scale values ​​comparing the importance of any target dimension with other target dimensions. The undetermined weights can be the weights used to evaluate the logistics path based on the calibration values; these are subjective weight coefficients that have not undergone consistency verification. The judgment matrix can be a matrix constructed from the undetermined weights of each target dimension. The consistency index can be the parameters used for consistency verification, which verifies the accuracy of the set calibration values, i.e., whether the importance represented by the set calibration values ​​is accurate. The index threshold can be used to determine whether the undetermined weights pass the consistency verification; the index threshold can be a user-defined value or a value determined based on experience.

[0116] After identifying multiple target dimensions in the logistics route, the scale value set for each target dimension can be obtained.

[0117] In practical applications, the scaling values ​​set by the user for each target dimension can be obtained, or the scaling values ​​for each target dimension can be determined based on experiments.

[0118] In practice, multiple professionals can score each target dimension to obtain a scale value for each target dimension.

[0119] After obtaining the scale value for each target dimension, the undetermined weight for each target dimension can be determined based on the scale value.

[0120] In practical applications, a judgment matrix can be constructed based on the scale value of each target dimension. This judgment matrix includes the scale values ​​between any target dimension and other target dimensions.

[0121] See Figure 6 , Figure 6 The diagram illustrates a judgment matrix according to an embodiment of the present invention, as shown below. Figure 6 As shown, the judgment matrix can include the scale value of each target dimension. Specifically, the data in the i-th row and j-th column is the scale value for comparing the i-th target dimension with the j-th target dimension, such as... Figure 6The data in the first column and first row of the judgment matrix is ​​the scale value for comparing the net height dimension with the net height dimension. Since the two are the same, the scale value is 1. The data in the second column and first row is the scale value for comparing the net height dimension with the cost dimension, and so on.

[0122] After obtaining the judgment matrix, the sum of the data in each column can be calculated, and the sum of each column can be used to normalize the data in each column, resulting in a normalized judgment matrix. After obtaining the normalized judgment matrix, the average value of each row can be determined, thus obtaining the undetermined weights for each target dimension.

[0123] In practical applications, before normalizing the judgment matrix, a backup of the judgment matrix can be performed for consistency verification.

[0124] After obtaining the undetermined weights for each target dimension, the determined undetermined weights can be weighted and calculated with the unnormalized judgment matrix to obtain the weighted result for each undetermined weight. For each undetermined weight, the undetermined weight can be divided by the weighted result to obtain the ratio of each undetermined weight to the weighted result. Then, the consistency index of the judgment matrix can be determined based on the ratio of each undetermined weight to the weighted result.

[0125] For example, the weights to be determined can be W = [0.558, 0.264, 0.057, 0.122]. The judgment matrix can be as follows: Figure 6 Given the judgment matrix shown, the weighted result for each undetermined weight can be: AW1= 1×0.558 + 3×0.264 + 7×0.057 + 5×0.122 = 2.387; AW2= 1 / 3×0.558 + 1×0.264 + 5×0.057 + 3×0.122 = 1.101; AW3= 1 / 7×0.558 + 1 / 5×0.264 + 1×0.057 + 1 / 3×0.122 = 0.244; AW4= 1 / 5×0.558 + 1 / 3×0.264 + 3×0.057 + 1×0.122 = 0.513; AW1 can be the weighted result of the undetermined weights of the first target dimension, and so on, AW4 can be the weighted result of the undetermined weights of the fourth target dimension.

[0126] For example, the ratio of each undetermined weight to the weighted result can be: λ1 = 2.387 / 0.558 = 4.278; λ² = 1.101 / 0.264 = 4.170; λ3 = 0.244 / 0.057 = 4.281; λ4 = 0.513 / 0.122 = 4.205; Wherein, λ1 can be the ratio of the undetermined weights of the first target dimension to its weighted result, and so on, λ4 can be the ratio of the undetermined weights of the fourth target dimension to its weighted result.

[0127] Specifically, the consistency index can be determined using the following formula: CI =

[0128] in, CI It can be used as a consistency indicator. It can be the average of the ratios of all undetermined weights to the weighted result, and n can be the total number of target dimensions.

[0129] For example, when λ1 is 4.278, λ2 is 4.170, λ3 is 4.281, and λ4 is 4.205, The answer is (4.278 + 4.170 + 4.281 + 4.205) / 4 = 4.234, which is... It is 4.234.

[0130] In practice, after obtaining the consistency index, the randomness index can also be determined based on the total number of target dimensions. Generally, when the total number of target dimensions is 3, the randomness index is 0.58; when the total number of target dimensions is 4, the randomness index is 0.9; and when the total number of target dimensions is 5, the randomness index is 1.12.

[0131] After determining the randomness index, the ratio of the consistency index to the randomness index can be determined. This ratio is then compared with a preset index threshold. If the ratio is less than the index threshold, the judgment matrix is ​​considered to have passed the consistency check, and the undetermined weights of the judgment matrix are output as subjective weight coefficients. If the ratio is greater than or equal to the index threshold, the judgment matrix is ​​considered to have failed the consistency check. The scale value in the judgment matrix can then be adjusted, and the consistency check can be repeated on the adjusted judgment matrix until the adjusted ratio is less than the index threshold.

[0132] After determining the subjective weight coefficient for each target dimension, the objective weight coefficient and the subjective weight coefficient for each target dimension can be merged to obtain the target weight coefficient corresponding to each target dimension.

[0133] In practical applications, for each target dimension, the objective weight coefficient and the subjective weight coefficient of the target dimension can be calculated as the sum of the objective weight coefficient and the subjective weight coefficient of the target dimension, which is the target weight coefficient of the target dimension. Alternatively, the objective weight coefficient and the subjective weight coefficient of the target dimension can be weighted according to preset weights to obtain the target weight coefficient of the target dimension. Thus, the target weight coefficient corresponding to each target dimension can be obtained.

[0134] S504 determines the comparison weights between each logistics path based on the dimensional parameters of each target dimension.

[0135] The comparison weights can include the comparison weights corresponding to each target dimension.

[0136] After obtaining the dimension parameters of each target dimension, a judgment matrix can be constructed based on the dimension parameters of each target dimension, and the weight of each row of data in the judgment matrix can be determined, which is the comparison weight corresponding to each target dimension, thereby obtaining the comparison weight between each logistics path.

[0137] In practical applications, the comparison weights of the judgment matrix constructed based on the dimension parameters can be determined by using the method described above to determine the undetermined weights of the judgment matrix.

[0138] S505 determines the total evaluation value for each logistics route based on the target weight coefficient and the comparison weight.

[0139] After obtaining the target weight coefficient for each target dimension and the corresponding comparison weight for each target dimension, for each logistics path, the target weight coefficient for each target dimension in the logistics path and the corresponding comparison weight for each target dimension can be weighted and calculated to obtain the total evaluation value of the logistics path, thus obtaining the total evaluation value of each logistics path.

[0140] It is important to understand that since the target weight coefficient is obtained by integrating objective and subjective weight coefficients, and the comparison weight corresponding to each target dimension is determined based on the actual dimension parameters in the logistics path, the integrated weight can be used to evaluate the comparison weight determined by the actual dimension parameters. This allows for the use of quantifiable indicators to evaluate each logistics path, reducing reliance on professionals and minimizing the impact of subjective factors by professionals on the evaluation of logistics paths, thereby improving the accuracy of determining logistics paths.

[0141] S506, Based on the overall evaluation value, determine the target logistics route from all logistics routes.

[0142] In this embodiment of the invention, multiple logistics paths of a building object are obtained, and dimension parameters of multiple target dimensions in the logistics paths are extracted. Based on the dimension parameters, an objective weight coefficient for each target dimension is determined. Based on the objective weight coefficient and a preset subjective weight coefficient, a target weight coefficient corresponding to the target dimension is determined. Based on the dimension parameters of each target dimension, a comparison weight between each logistics path is determined. Based on the target weight coefficient and the comparison weight, a total evaluation value for each logistics path is determined. Based on the total evaluation value, a target logistics path is determined from all logistics paths. This enables the determination of a superior logistics path as the target logistics path based on evaluation values ​​of different dimensions, reducing reliance on professional personnel, improving the accuracy of logistics path determination, and reducing the number of modifications to the target logistics path compared to other logistics paths, thus improving the efficiency of logistics path determination.

[0143] See Figure 7 , Figure 7 The diagram shows a structural schematic of a logistics path determination device according to an embodiment of this application. The device may specifically include the following modules: Module 701 is used to obtain multiple logistics paths of building objects; Extraction module 702 is used to extract dimension parameters of multiple target dimensions in the extraction flow path; Evaluation module 703 is used to determine the total evaluation value of each logistics route based on the weight coefficients corresponding to each target dimension and the dimension parameters of each target dimension. Module 704 is used to determine the target logistics route from all logistics routes based on the overall evaluation value. In one implementation, the determining module 704 described above can also be used for: Based on the dimension parameters, determine the target dimension parameters for each target dimension; Determine the difference between the dimensional parameters in each logistics path and the target dimensional parameters; Based on the overall evaluation value and the difference value, the target logistics route is determined from all logistics routes.

[0144] In one implementation, the target dimension parameters include positive target dimension parameters and negative target dimension parameters. Based on the dimension parameters, the aforementioned determining module 704 can also be used for: Generate a normalized matrix based on the dimension parameters; the normalized matrix includes the normalized value of each dimension parameter. The standardized matrix is ​​weighted according to the weight coefficients corresponding to the target dimensions to obtain the positive and negative target dimension parameters for each target dimension.

[0145] In one implementation, the difference values ​​include positive difference values ​​and negative difference values, and the aforementioned determining module 704 can also be used for: Based on the positive and negative difference values, determine the relative difference value for each logistics route; The relative difference value and the total evaluation value are weighted according to the preset weights to obtain the relative evaluation value of each logistics route; The logistics path with the highest relative evaluation value is determined as the target logistics path.

[0146] In one implementation, the evaluation module 703 described above can also be used for: Based on the dimension parameters, determine the objective weight coefficient for each target dimension; The target weight coefficients for each target dimension are determined based on the objective weight coefficients and the preset subjective weight coefficients. The subjective weight coefficients are determined based on the relative weights between each target dimension, and the relative weights are determined based on subjective factors. Based on the dimensional parameters of each target dimension, determine the comparison weight between each logistics path; where the comparison weight includes the comparison weight corresponding to each target dimension; The total evaluation value for each logistics route is determined based on the target weight coefficient and the comparison weight.

[0147] In one implementation, the acquisition module 701 can also be used to acquire the scale value set for each target dimension before determining the target weight coefficient corresponding to the target dimension based on the objective weight coefficient and the preset subjective weight coefficient. In one implementation, the determining module 704 described above can also be used for: Based on the scaling values, determine the undetermined weights for each target dimension, and determine the consistency index of the judgment matrix based on the undetermined weights. When the consistency index is less than the preset index threshold, the undetermined weight is determined as the subjective weight coefficient. When the consistency index is greater than or equal to the index threshold, adjust the scale value until the consistency index is less than the index threshold.

[0148] In one implementation, the evaluation module 703 described above can also be used for: Determine the standardized value of each dimension parameter, and determine the entropy value of each target dimension based on the standardized value; Based on the entropy value of each target dimension, determine the objective weight coefficient for each target dimension.

[0149] In this embodiment of the invention, multiple logistics paths of a building object are obtained, and the dimension parameters of multiple target dimensions in the logistics paths are extracted. Based on the weight coefficients corresponding to each target dimension and the dimension parameters of each target dimension, the total evaluation value of each logistics path is determined. Based on the total evaluation value, the target logistics path is determined from all logistics paths. This enables the determination of the optimal logistics path as the target logistics path based on the evaluation values ​​of different dimensions, reduces the reliance on professional personnel, improves the accuracy of determining logistics paths, and increases the efficiency of determining logistics paths by modifying the target logistics path less than modifying other logistics paths.

[0150] It should be noted that the information interaction and execution process between the above-mentioned devices are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0151] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0152] See Figure 8 , Figure 8 This application provides a structural block diagram of an electronic device according to an embodiment of the present application, as shown below. Figure 8 As shown, this embodiment provides an electronic device 81, which includes at least one processor 811, a memory 812, and a computer program 8121 stored in the memory 812 and executable on at least one processor 811. When the processor 811 executes the computer program 8121, it implements the steps in any of the above-described method embodiments.

[0153] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can implement the steps in any of the above method embodiments.

[0154] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the various method embodiments.

[0155] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium.

[0156] The above detailed description is a specific description of feasible embodiments of the present invention. These embodiments are not intended to limit the patent scope of the present invention. All equivalent implementations or modifications that do not depart from the present invention should be included in the patent scope of this case.

Claims

1. A method for determining a logistics route, characterized in that, The method includes: Obtain multiple logistics paths for a building object, and extract dimensional parameters for multiple target dimensions from the logistics paths; The total evaluation value of each logistics path is determined based on the weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension. Based on the overall evaluation value, the target logistics path is determined from all the logistics paths.

2. The method for determining the logistics route as described in claim 1, characterized in that, The method further includes: Based on the dimension parameters, determine the target dimension parameters for each target dimension; Determine the difference between the dimensional parameter and the target dimensional parameter in each of the logistics paths; The process of determining the target logistics path from all the logistics paths based on the overall evaluation value includes: Based on the total evaluation value and the difference value, the target logistics path is determined from all the logistics paths.

3. The method for determining the logistics route as described in claim 2, characterized in that, The target dimension parameters include positive target dimension parameters and negative target dimension parameters. Determining the target dimension parameter for each target dimension based on the dimension parameters includes: A standardized matrix is ​​generated based on the dimension parameters; wherein the standardized matrix includes the standardized value of each dimension parameter; The standardized matrix is ​​weighted according to the weight coefficients corresponding to the target dimensions to obtain the positive target dimension parameters and negative target dimension parameters for each target dimension.

4. The method for determining the logistics route as described in claim 3, characterized in that, The difference values ​​include positive and negative difference values. The process of determining the target logistics path from all the logistics paths based on the total evaluation value and the difference values ​​includes: Based on the positive and negative difference values, determine the relative difference value for each logistics path; The relative difference value and the total evaluation value are weighted according to preset weights to obtain the relative evaluation value of each logistics path; The logistics path with the highest relative evaluation value is determined as the target logistics path.

5. The method for determining the logistics route as described in any one of claims 1 to 4, characterized in that, The step of determining the total evaluation value of each logistics path based on the weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension includes: Based on the dimension parameters, determine the objective weight coefficient for each target dimension; Based on the objective weight coefficient and the preset subjective weight coefficient, the target weight coefficient corresponding to the target dimension is determined; wherein, the subjective weight coefficient is determined based on the relative weight between each target dimension, and the relative weight is determined based on subjective factors; Based on the dimension parameters of each target dimension, the comparison weight between each logistics path is determined; wherein, the comparison weight includes the comparison weight corresponding to each target dimension; The total evaluation value for each logistics route is determined based on the target weight coefficient and the comparison weight.

6. The method for determining the logistics route as described in claim 5, characterized in that, Before determining the target weight coefficient corresponding to the target dimension based on the objective weight coefficient and the preset subjective weight coefficient, the method further includes: Obtain the scale value set for each of the target dimensions; Based on the scale value, determine the undetermined weights for each of the target dimensions, and determine the consistency index of the judgment matrix based on the undetermined weights; When the consistency index is less than the preset index threshold, the undetermined weight is determined to be a subjective weight coefficient. When the consistency index is greater than or equal to the index threshold, the scaling value is adjusted until the consistency index is less than the index threshold.

7. The method for determining the logistics route as described in claim 5, characterized in that, The step of determining the objective weight coefficient for each target dimension based on the dimension parameters includes: Determine the standardized value of each of the dimension parameters, and determine the entropy value of each of the target dimensions based on the standardized values; Based on the entropy value of each target dimension, determine the objective weight coefficient of each target dimension.

8. A device for determining a logistics route, characterized in that, The device includes: The acquisition module is used to acquire multiple logistics paths for building objects; The extraction module is used to extract dimensional parameters of multiple target dimensions in the logistics path; The evaluation module is used to determine the total evaluation value of each logistics path based on the weight coefficient corresponding to each target dimension and the dimension parameter of each target dimension. A determination module is used to determine a target logistics path from all the logistics paths based on the total evaluation value.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for determining the logistics path as described in any one of claims 1 to 7.

10. A computer program product, said computer program product storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for determining the logistics path as described in any one of claims 1 to 7.

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