Distribution center site selection method considering fuel consumption of transport vehicle

Abstract

The invention discloses a distribution center site selection method considering the fuel consumption of a transport vehicle, and the method comprises the steps: collecting the geographic position information of express stations, the demand quantity of shared express boxes of each express station, and the to-be-recovered quantity of the express stations; shared express box recovery information such as shared express box recovery rate, shared express box transportation loss rate, customer shared express box loss rate, express site shared express box loss rate and the like, vehicle running information such as transportation vehicle maximum capacity, vehicle basic rent, vehicle running speed and the like are added, and vehicle oil consumption information aiming at different conditions is added at the same time. The method comprises the following factors: road condition oil consumption for collecting and transporting the shared express boxes from each express station to a distribution center by a transport vehicle, internal transportation oil consumption of the distribution center, oil consumption during loading and unloading of the shared express boxes, and the like, according to the method, an improved whale optimization algorithm is used for solving a distribution center site selection model considering the oil consumption of the transport vehicle; therefore, the distribution center site selection method which is low in fuel consumption index of the transport vehicle and low in total logistics cost is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of forward and reverse logistics distribution management of shared express boxes, and in particular to a method for selecting a diversion center site taking into account the fuel consumption of transport vehicles. Background Art

[0002] With the booming e-commerce, the volume of express delivery business continues to rise, which puts higher requirements on the efficiency, cost control and environmental performance of express delivery systems. The traditional express delivery model usually relies on a large number of transport vehicles for the distribution and delivery of goods. In order to meet these challenges, the express delivery industry has begun to explore the application of shared express boxes, aiming to achieve resource conservation and environmental protection by reducing the use of packaging materials and reusing express boxes.

[0003] However, relying solely on the use of shared express boxes is not enough to fully solve the problem of resource waste in express delivery. Factors such as the distance traveled, load, and route planning of transport vehicles directly affect the fuel consumption level, and these factors largely depend on the location and layout of the express distribution center. Reasonable location selection can not only shorten the transportation distance, reduce empty and repeated transportation, thereby reducing fuel consumption, but also improve delivery efficiency and enhance customer satisfaction.

[0004] In the current express delivery system, the location of express distribution centers is often based on empirical judgment or simple cost-benefit analysis, and the key factor of fuel consumption of transport vehicles is rarely considered. This practice has led to the unreasonable location of some distribution centers, and transport vehicles frequently travel back and forth to remote or inconvenient areas, resulting in high fuel consumption, low efficiency, and increased operating costs.

[0005] In order to solve this problem, the present invention proposes a method for selecting a distribution center location that takes into account the fuel consumption of transport vehicles. The method aims to optimize the express delivery network, reduce the fuel consumption of transport vehicles, and improve the overall delivery efficiency through scientific site selection decisions. Summary of the invention

[0006] In order to overcome the above problems or at least partially solve the above problems, the present invention provides a method for selecting a diversion center location taking into account the fuel consumption of transport vehicles, so as to reduce costs.

[0007] The technical solution adopted by the present invention is: a method for selecting a diversion center location taking into account the fuel consumption of transport vehicles, comprising the following steps:

[0008] Step S1: Obtaining express station information, shared express box recycling information, vehicle operation information, and vehicle fuel consumption information under different circumstances;

[0009] Step S2: Establishing a total transportation cost evaluation mechanism that takes vehicle fuel consumption into consideration, and adding a penalty mechanism to the evaluation mechanism to improve efficiency;

[0010] S3: Combine the express station information, shared express box recycling information, vehicle operation information and vehicle fuel consumption information under different circumstances to design a diversion center location model that takes into account the fuel consumption of transportation vehicles;

[0011] S4: Based on the established diversion center location selection model, an improved whale optimization algorithm is designed to optimize the location selection method, and the total transportation cost evaluation mechanism considering vehicle fuel consumption is combined to obtain the diversion center location selection result with the optimal total cost.

[0012] Furthermore, the express station location information of the present invention includes the geographical location information of the express station, the demand for shared express boxes at each express station, and the amount to be recycled. The express station location information is V i =(v 1 , v 2 ,v 3 , v 4 ), where v 1 Indicates longitude v 2 Indicates latitude, v 3 represents the demand for shared express boxes, v 4 Indicates the amount of shared express boxes waiting to be recycled.

[0013] Furthermore, the shared express box recycling information of the present invention includes: the shared express box recycling rate, the shared express box loss rate during transportation, the customer shared express box loss rate, and the express station shared express box loss rate.

[0014] Furthermore, the vehicle operation information of the present invention includes the maximum capacity of the transport vehicle, the basic rental of the vehicle, and the driving speed of the vehicle. The vehicle fuel consumption information for different situations includes the road fuel consumption of the transport vehicle collecting and transporting the shared express boxes from various express stations to the distribution center, the internal transportation fuel consumption of the distribution center, and the fuel consumption when loading and unloading the shared express boxes.

[0015] Furthermore, the present invention establishes a total transportation cost evaluation mechanism that takes vehicle fuel consumption into consideration, where the vehicle fuel consumption evaluation index is S and the evaluation mechanism set is:

[0016] B=(B 1 ,B 2 ,B 3 ),

[0017] Among them B 1 Describe the shared express box and score it according to the actual situation. 2 is the freight to be paid, B3 is the penalty for shared express boxes, and scores are given according to the actual situation. Let factor set B = (B 1 ,B 2 ,B 3 The comprehensive score set of each factor in ) is B = (B′ 1 ,B′ 2 , B′3 ), B′ n The maximum estimated transportation cost is defined by the shared express box recycling merchants themselves, and the total transportation cost evaluation mechanism b h ,

[0018] b h =B′ 1 +B′ 2 +(B′ n -B′ 3 )

[0019]

[0020] Among them, F i represents the fuel consumption rate from the ith express station to the distribution center, D i represents the length of the transportation path from the ith express station to the distribution center, G fuel Indicates the unit price of fuel, H i represents the road condition coefficient from the ith express station to the distribution center, Q i represents the loading and unloading cost coefficient of the ith express station, Q maintenance represents the unit loading and unloading cost, L i represents the internal transportation coefficient of the i-th express station vehicle in the distribution center, L maintenance Represents the internal transportation cost of the distribution center.

[0021] Furthermore, after each transportation, the present invention evaluates the diversion center according to the evaluation mechanism, selects the path with the lowest total fuel consumption cost, and ensures the stability of fuel consumption of the transportation vehicles.

[0022] Furthermore, the vehicle fuel consumption evaluation index of the present invention is determined by vehicle performance, driving behavior, road conditions and load conditions, and is used to assist the vehicle fuel consumption evaluation mechanism.

[0023] S=γ×VPFCI+δ×DBFCI+μ×RCFCI+ρ×LCFCI

[0024] Where S is the total score, γ, δ, μ, ρ represent the weight coefficients of each index, and their sum is 1, that is, γ+δ+μ+ρ=1, where VPFCI represents the vehicle performance fuel consumption index, and its formula is:

[0025]

[0026] FCR stands for fuel consumption per 100 kilometers, and its formula is: FCR represents the fuel consumption per 100 kilometers, and EEI represents the engine efficiency index, which is used to reflect the working status of the engine. It is the ratio of the actual power of the engine to the rated power. The formula is: ω 1 and ω2 is the weight coefficient, set to the default value ω 1 =0.6,ω 2 =0.4.

[0027] DBFCI stands for driving behavior fuel consumption index, and its formula is:

[0028] DBFCI=ω 3 ×(e HAT )+ω 4 ×(e HDT )+ω 5 ×SDR,

[0029] ω 3 ,ω 4 ,ω 5 is the weight coefficient, set to the default value: ω 3 =0.4,ω 4 =0.5,ω 5 =0.1, HAT represents the number of sudden accelerations, i.e., the number of times the vehicle suddenly accelerates per unit time; HDT represents the number of sudden decelerations, i.e., the number of times the vehicle suddenly decelerates per unit time; SDR represents the smooth driving rate, which reflects the smoothness of the vehicle speed change during driving.

[0030] Among them, RCFCI represents the fuel consumption index under road conditions, and its formula is:

[0031] RCFCI=ω 6 ×(1-CI)+ω 7 ×AS

[0032] ω 6 ,ω 7 is the weight coefficient, set to the default value: ω 6 =0.4,ω 7 =0.6, Cl represents the congestion level, which is an indicator used to reflect the degree of road congestion, and AS represents the average vehicle speed, which represents the average speed of the vehicle during driving.

[0033] Among them, LCFCI represents the fuel consumption index under load conditions, and its formula is:

[0034]

[0035] T M Indicates the actual load. Indicates full load, C M Indicates fuel consumption.

[0036] S is the vehicle fuel consumption evaluation index, which is determined by vehicle performance, driving behavior, road conditions and load conditions, and is used to assist the vehicle fuel consumption evaluation mechanism.

[0037] S=γ×VPFCI+δ×DBFCI+μ×RCFCI+ρ×LCFCI

[0038] Where S is the total score, γ, δ, μ, ρ represent the weight coefficients of each index, and their sum is 1, that is, γ+δ+μ+ρ=1, where VPFCI represents the vehicle performance fuel consumption index, and its formula is:

[0039]

[0040] FCR stands for fuel consumption per 100 kilometers, and its formula is: FCR' represents the fuel consumption benchmark per 100 kilometers, and EEI represents the engine efficiency index, which is used to reflect the working status of the engine. It is the ratio of the actual power of the engine to the rated power. The formula is: ω 1 and ω 2 is the weight coefficient, set to the default value ω 1 =0.6,ω 2 =0.4.

[0041] DBFCI stands for driving behavior fuel consumption index, and its formula is:

[0042] DBFCI=ω 3 ×(e HAT )+ω 4 ×(e HDT )+ω 5 ×SDR,

[0043] ω 3 ,ω 4 ,ω 5 is the weight coefficient, set to the default value: ω 3 =0.4,ω 4 =0.5,ω 5 =0.1, HAT represents the number of sudden accelerations, i.e. the number of times the vehicle suddenly accelerates per unit time, HDT represents the number of sudden decelerations, i.e. the number of times the vehicle suddenly decelerates per unit time, and SDR represents the smooth driving rate, which reflects the smoothness of the vehicle speed change during driving.

[0044] Among them, RCFCI represents the fuel consumption index under road conditions, and its formula is:

[0045] RCFCI=ω 6 ×(1-CI)+ω 7 ×AS

[0046] ω 6 ,ω 7 is the weight coefficient, set to the default value: ω 6 =0.4,ω 7=0.6, Cl represents the congestion level, which is an indicator used to reflect the degree of road congestion, and AS represents the average vehicle speed, which represents the average speed of the vehicle during driving.

[0047] Among them, LCFCI represents the fuel consumption index under load conditions, and its formula is:

[0048]

[0049] T M Indicates the actual load. Indicates full load, C M Indicates fuel consumption.

[0050] As a method for selecting a distribution center location considering vehicle fuel consumption according to the present invention, the distribution center location selection model includes:

[0051] The objective function is:

[0052] minC=C 1 +C 2 +C 3 +C4+C 5

[0053] Among them, C 1 Represents the basic cost, including the construction cost of the distribution center, the purchase cost of the transport vehicle, the operating cost of the distribution center, the loss cost of the vehicle, etc. K represents the value of the basic cost, and its value remains unchanged. The basic cost expression is as follows:

[0054]

[0055] Among them, C 2 represents the penalty mechanism cost, including the waiting cost of the vehicle waiting for recycling at the recycling station and the delay cost of using the shared express box, that is, the delay cost of recycling the vehicle. Let p a represents the waiting cost of the recovery vehicle on site, P a represents the maximum non-penalty waiting cost in the recovery vehicle area, p b represents the delay cost of the recycling station vehicle per unit time, P b represents the maximum non-penalty delay cost in the recovery vehicle area, let t a It represents the time when the recycling station vehicle arrives at the courier station a waiting to collect the shared courier boxes to be recycled. The penalty mechanism cost is as follows:

[0056]

[0057] Among them C 3 is the recycling cost of the shared express box, which includes the damage cost of the shared express box, the recycling cost of the shared express box, the loading and unloading cost of the shared express box, etc. arepresents the amount of shared express boxes to be recycled at express station a, L represents the loss rate of shared express boxes during the delivery process, M represents the cost of a single shared express box, and H represents the sum of the recycling cost and loading and unloading cost of the shared express box. The recycling cost expression is as follows:

[0058]

[0059] Among them C 4 is the transportation cost of the shared express box in the forward and reverse logistics transportation process, S a represents the distance from express station a to the shared express box distribution center, K a Z represents the amount of shared express boxes to be recycled at express station a, that is, the amount of shared express boxes to be transported at each station. a represents the demand of express delivery station a for shared express boxes that have been recycled, c a It represents the logistics cost required for the transportation of shared express boxes within a unit distance. The transportation cost expression is as follows:

[0060]

[0061] Among them C 5 is the classification cost of the shared express box, and F represents the classification time cost of a single shared express box. The classification cost is as follows:

[0062] C 5 =K a *F

[0063] As a method for selecting a diversion center location considering vehicle fuel consumption according to the present invention, the constraint condition is:

[0064] Condition 1: The total weight of the shared express boxes loaded on the transport vehicle cannot exceed the vehicle load, expressed as:

[0065] ∑ a＝1 X a ≤X all ,

[0066] Condition 2: The volume of cargo loaded on the vehicle cannot exceed the vehicle capacity, expressed as:

[0067]

[0068] Condition 3: Must comply with local environmental laws and urban planning strategies;

[0069] Condition 4: The amount of shared express boxes recycled should always be less than the capacity of the recycling center;

[0070]

[0071] As a method for selecting a diversion center location taking vehicle fuel consumption into consideration according to the present invention, wherein:

[0072] In order to improve the problem of whales falling into local optimality in the later stage, an improved whale optimization algorithm is designed according to the established diversion center location model. The improved whale optimization algorithm (ZWOA) is used to improve the target mathematical model to obtain the final location plan of the shared express box diversion center. The improved whale optimization algorithm (ZWOA) includes:

[0073] A local search phase is added after each main loop iteration. Local search is implemented by generating multiple candidate solutions near the leader position and evaluating these solutions. In the local search phase, a candidate solution is generated and checked to see if its fitness value is better than the current leader. If so, the leader position and score are updated, which helps the algorithm to search more carefully in a local area of ​​the search space, thereby increasing the possibility of finding the global optimal solution.

[0074] Candidate_pos=X leader +(u b -l b )*(r-0.5),

[0075] Among them, r represents a random number between [0, 1], u b and l b They represent the upper and lower bounds of the search space respectively.

[0076] As a method for selecting a diversion center location taking vehicle fuel consumption into consideration according to the present invention, wherein:

[0077] The introduction of an adaptive step size adjustment factor makes the algorithm more flexible. The specific steps are as follows:

[0078] Step 1: Introduce an algorithm parameter a, which represents the spiral shape and shrinking mechanism that affects the surrounding prey. It changes nonlinearly with the number of iterations, rather than linearly as in the standard WOA, which helps the algorithm better balance global exploration and local development capabilities during the search process. The formula for α is:

[0079]

[0080] Among them, α initial and α final are the initial and final values ​​of α, t is the current number of iterations, and Max_iter is the maximum number of iterations.

[0081] Step 2: Introduce an algorithm parameter a2, which is used to calculate the parameters of the spiral shape. It changes nonlinearly with the number of iterations, rather than linearly as in the standard WOA, which helps the algorithm better balance global exploration and local development capabilities during the search process. 2 The formula is:

[0082]

[0083] Among them, β initial and β final They are α 2 The initial and final values ​​of .

[0084] Step 3: Introduce a dynamically adjusted algorithm parameter b to affect the shrinkage rate of the spiral shape, and change the tightness of the spiral shape as the number of iterations changes. This helps improve the global search capability.

[0085] The expression formula of b is:

[0086]

[0087] where b initial and b final are the initial and final values ​​of b respectively.

[0088] As a method for selecting a diversion center location taking vehicle fuel consumption into consideration according to the present invention, wherein:

[0089] For situations that exceed the search space boundary, the improved whale optimization algorithm will adjust its position back to the boundary. This boundary handling mechanism ensures that the algorithm always stays within the valid search space during the search process.

[0090] The position of the whale in a certain dimension is x i The lower bound of the search space in this dimension is L i , the upper bound is U i If the whale's new position x′ i If it exceeds the boundary of the search space, it needs to be adjusted. The adjusted position x″ i for:

[0091]

[0092] If the whale’s new position x′ i Less than the lower bound L i , then adjust its position to the lower bound L i ; If the whale’s new position x′ i In the lower bound L i and upper bound U i (including the boundary), then keep its position unchanged; if the new position of the whale x′ iGreater than the upper bound U i , then adjust its position to the upper bound U i .

[0093] The improved whale optimization algorithm ZWOA also records the fitness value of the leader (i.e. the quality of the optimal solution) after each iteration and stores these values ​​in the convergence_curve array. This helps analyze the convergence performance and stability of the algorithm.

[0094] As a method for selecting a diversion center location taking vehicle fuel consumption into consideration according to the present invention, wherein:

[0095] The improved whale optimization algorithm is used to solve the objective function of the diversion center location selection method model, and the steps include the following:

[0096] 1) Algorithm initialization and parameter definition

[0097] During the initialization phase of the algorithm, the location of each whale is set to a random value of the decision variable that is within the given search space (i.e., the range of possible locations).

[0098] 2) Fitness evaluation For each whale position (i.e., each candidate diversion center position), its fitness value is calculated using the objective function.

[0099] 3) Whale location updates

[0100] According to the principle of the whale optimization algorithm, the whale will search around the current optimal position (that is, the current optimal diversion center position), randomly select the positions of other whales as reference points, and update its own position in a spiral manner.

[0101] 4) Local Search and Evaluation

[0102] Generate candidate solutions within a certain range of the current optimal position, evaluate their fitness values, and determine whether to exit the loop. When the algorithm converges or reaches the maximum number of iterations, output the optimal diversion center position and its corresponding fitness value. Otherwise, return to the above step 2).

[0103] 5) Site selection decision Based on the optimal diversion center location output by the algorithm, the final site selection decision and the minimum value C are made. MIN .

[0104] Beneficial effects:

[0105] 1. The present invention adopts an improved whale optimization algorithm, which optimizes the algorithm to a certain extent at each stage, so that the algorithm always remains in the effective search space during the search process, and can better balance the global exploration and local development capabilities during the search process, and can provide a reasonable diversion center site selection plan.

[0106] 2. The present invention solves the diversion center site selection model that takes into account the fuel consumption of transport vehicles through an improved whale optimization algorithm to obtain a diversion center site selection method that meets the requirements of low fuel consumption indicators for transport vehicles and low total logistics costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0107] Figure 1 This is the forward and reverse logistics distribution flow chart proposed by the present invention.

[0108] Figure 2 This is a global specific flow chart of the recycling process proposed by the present invention.

[0109] Figure 3 Comparison chart of the number of iterations between the improved whale optimization algorithm (ZWOA) and the BWO, DBO, BOA, SCA, and WOA algorithms.

[0110] Figure 4 For specific implementation map.

[0111] Figure 5 This is the site selection and cost comparison chart of the improved whale optimization algorithm of the present invention.

[0112] Figure 6 Schematic diagram of the reverse logistics planning scheme of the improved whale optimization algorithm of the present invention. DETAILED DESCRIPTION

[0113] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only for illustration and are not intended to limit the present invention.

[0114] A method for selecting a distribution center location taking into account the fuel consumption of transport vehicles, the method comprising the following steps:

[0115] Step S1: Obtain express station information, shared express box recycling information, and vehicle operation information.

[0116] Step S2: Obtain vehicle fuel consumption information and establish a total transportation cost evaluation mechanism that takes vehicle fuel consumption into consideration.

[0117] Step S3: Design a diversion center location model that takes into account the fuel consumption of transportation vehicles by combining factors such as express station information, shared express box recycling information, vehicle operation information, and vehicle fuel consumption information under different circumstances.

[0118] Step S4: Based on the established diversion center location selection model, an improved whale optimization algorithm is designed to optimize the location selection method, and the total transportation cost evaluation mechanism for vehicle fuel consumption is combined to obtain the diversion center location selection result with the optimal total cost.

[0119] The specific implementation of the above-mentioned multimodal transport scheme research for the Yangtze River Economic Belt provided by the present invention is described in detail below through a specific embodiment.

[0120] like Figure 1 As shown, the present invention provides a method for selecting a diversion center location taking into account the fuel consumption of transportation vehicles, comprising the following steps:

[0121] Step 1: Collect express station information, shared express box recycling information, and vehicle operation information.

[0122] The express station information includes the longitude and latitude of the express station location, the demand for shared express boxes at each express station, and the amount to be recycled.

[0123] The shared express box recycling information includes the shared express box recycling rate, the shared express box loss rate during transportation, the customer shared express box loss rate, and the shared express box loss rate at express stations.

[0124] Vehicle operation information includes the maximum capacity of the transport vehicle, the basic rental fee of the vehicle, and the vehicle's driving speed.

[0125] Step 2: Collect vehicle fuel consumption information.

[0126] Vehicle fuel consumption information includes factors such as the road conditions fuel consumption when transporting vehicles to collect and transport shared express boxes from various express stations to the diversion center, the internal transportation fuel consumption of the diversion center, and the fuel consumption when loading and unloading shared express boxes.

[0127] The total transportation cost evaluation mechanism B of the vehicle fuel consumption refers to the evaluation based on the description of the shared express box transported by the vehicle, the freight to be paid, and the penalty for the shared express box. The comprehensive score of the vehicle fuel consumption is also combined with the vehicle fuel consumption evaluation index S, which is determined by vehicle performance, driving behavior, road conditions, and load conditions.

[0128] Step 3: Establish the total transportation cost evaluation mechanism B of vehicle fuel consumption and the vehicle fuel consumption evaluation index S. The evaluation mechanism B is as follows:

[0129] B=(B 1 , B 2 , B 3 ),

[0130] Among them B 1 Describe the shared express box and score it according to the actual situation. 2 is the freight to be paid, B3 is the penalty for sharing express boxes, and scores are given according to the actual situation. Let factor set B = (B 1 , B 2 , B 3 The comprehensive score set of each factor in ) is B = (B′ 1 , B′ 2 , B′ 3), B′ n The maximum estimated transportation cost is defined by the shared express box recycling merchants themselves, and the total transportation cost evaluation mechanism b h ,

[0131] b h =B′ 1 +B′ 2 +(B′ n -B′ 3 )

[0132]

[0133] Among them, F i represents the fuel consumption rate from the ith express station to the distribution center, D i represents the length of the transportation path from the ith express station to the distribution center, G fuel Indicates the unit price of fuel, H i represents the road condition coefficient from the ith express station to the distribution center, Q i represents the loading and unloading cost coefficient of the ith express station, Q maintenance represents the unit loading and unloading cost, L i represents the internal transportation coefficient of the i-th express station vehicle in the distribution center, L maintenance Represents the internal transportation cost of the distribution center.

[0134] After each transport, the diversion center will be evaluated according to the evaluation mechanism to select the route with the lowest total fuel consumption cost and ensure the stability of fuel consumption of transport vehicles.

[0135] The vehicle fuel consumption evaluation index S is determined by vehicle performance, driving behavior, road conditions and load conditions, and is used to assist the vehicle fuel consumption evaluation mechanism.

[0136] S=γ×VPFCI+δ×DBFCI+μ×RCFCI+ρ×LCFCI

[0137] Where S is the total score, γ, δ, μ, ρ represent the weight coefficients of each index, and their sum is 1, that is, γ+δ+μ+ρ=1, where VPFCI represents the vehicle performance fuel consumption index, and its formula is:

[0138]

[0139] FCR stands for fuel consumption per 100 kilometers, and its formula is: FCR' represents the fuel consumption benchmark per 100 kilometers, and EEI represents the engine efficiency index, which is used to reflect the working status of the engine. It is the ratio of the actual power of the engine to the rated power. The formula is: ω 1 and ω 2 is the weight coefficient, set to the default value ω1 =0.6,ω 2 =0.4.

[0140] DBFCI stands for driving behavior fuel consumption index, and its formula is:

[0141] DBFCI=ω 3 ×(e HAT )+ω 4 ×(e HDT )+ω 5 ×SDR,

[0142] ω 3 ,ω 4 ,ω 5 is the weight coefficient, set to the default value: ω 3 =0.4,ω 4 =0.5,ω 5 =0.1, HAT represents the number of sudden accelerations, i.e., the number of times the vehicle suddenly accelerates per unit time; HDT represents the number of sudden decelerations, i.e., the number of times the vehicle suddenly decelerates per unit time; SDR represents the smooth driving rate, which reflects the smoothness of the vehicle speed change during driving.

[0143] Among them, RCFCI represents the fuel consumption index under road conditions, and its formula is:

[0144] RCFCI=ω 6 ×(1-CI)+ω 7 ×AS

[0145] ω 6 ,ω 7 is the weight coefficient, set to the default value: ω 6 =0.4,ω 7 =0.6, Cl represents the congestion level, which is an indicator used to reflect the degree of road congestion, and AS represents the average vehicle speed, which represents the average speed of the vehicle during driving.

[0146] Among them, LCFCI represents the fuel consumption index under load conditions, and its formula is:

[0147]

[0148] T M Indicates the actual load. Indicates full load, C M Indicates fuel consumption.

[0149] Step 4: Establish a diversion center site selection model.

[0150] The objective function is:

[0151] minC=C 1 +C 2+C 3 +C 4 +C 5

[0152] Among them, C 1 Represents the basic cost, including the construction cost of the distribution center, the purchase cost of the transport vehicle, the operating cost of the distribution center, the loss cost of the vehicle, etc. K represents the value of the basic cost, and its value remains unchanged. The basic cost expression is as follows:

[0153]

[0154] Among them, C 2 represents the penalty mechanism cost, including the waiting cost of the vehicle waiting for recycling at the recycling station and the delay cost of using the shared express box, that is, the delay cost of recycling the vehicle. Let p a represents the waiting cost of the recovery vehicle on site, P a represents the maximum non-penalty waiting cost in the recovery vehicle area, p b represents the delay cost of the recycling station vehicle per unit time, P b represents the maximum non-penalty delay cost in the recovery vehicle area, let t a It represents the time when the recycling station vehicle arrives at the courier station a waiting to collect the shared courier boxes to be recycled. The penalty mechanism cost is as follows:

[0155]

[0156] Among them C 3 is the recycling cost of the shared express box, which includes the damage cost of the shared express box, the recycling cost of the shared express box, the loading and unloading cost of the shared express box, etc. a represents the amount of shared express boxes to be recycled at express station a, L represents the loss rate of shared express boxes during the delivery process, M represents the cost of a single shared express box, and H represents the sum of the recycling cost and loading and unloading cost of the shared express box. The recycling cost expression is as follows:

[0157]

[0158] Among them C 4 is the transportation cost of the shared express box in the forward and reverse logistics transportation process, S a represents the distance from express station a to the shared express box distribution center, K a Z represents the amount of shared express boxes to be recycled at express station a, that is, the amount of shared express boxes to be transported at each station. a represents the demand of express delivery station a for shared express boxes that have been recycled, c a It represents the logistics cost required for the transportation of shared express boxes within a unit distance. The transportation cost expression is as follows:

[0159]

[0160] Among them C 5 is the classification cost of the shared express box, and F represents the classification time cost of a single shared express box. The classification cost is as follows:

[0161] C 5 =K a *F

[0162] Compared with the previous site selection model, this model adds a penalty mechanism for classified discussion. At the same time, the distribution center site selection model also adds the shared express box classification cost C 5 It will also help to ease the clutter in the process.

[0163] The constraints of the diversion center location model are:

[0164] Condition 1: The total weight of the shared express boxes loaded on the transport vehicle cannot exceed the vehicle load, expressed as:

[0165] ∑ a＝1 X a ≤X all ,

[0166] Condition 2: The volume of cargo loaded on the vehicle cannot exceed the vehicle capacity, expressed as:

[0167]

[0168] Condition 3: Must comply with local environmental laws and urban planning strategies;

[0169] Condition 4: The amount of shared express boxes recycled should always be less than the capacity of the recycling center;

[0170]

[0171] Step 5: Solve the objective function using the improved whale optimization algorithm

[0172] The specific steps include the following:

[0173] 1) Algorithm initialization and parameter definition

[0174] During the initialization phase of the algorithm, the location of each whale is set to a random value of the decision variable that is within the given search space (i.e., the range of possible locations).

[0175] 2) Fitness evaluation

[0176] For each whale position (i.e., each candidate diversion center position), its fitness value is calculated using the objective function.

[0177] 3) Whale location updates

[0178] According to the principle of the whale optimization algorithm, the whale will search around the current optimal position (that is, the current optimal diversion center position), randomly select the positions of other whales as reference points, and update its own position in a spiral manner.

[0179] The introduction of an adaptive step size adjustment factor makes the algorithm more flexible. The specific steps are as follows:

[0180] Step 1: Introduce an algorithm parameter a, which represents the spiral shape and shrinking mechanism that affects the surrounding prey. It changes nonlinearly with the number of iterations, rather than linearly as in the standard WOA, which helps the algorithm better balance global exploration and local development capabilities during the search process. The formula for α is:

[0181]

[0182] Among them, α initial and α final are the initial and final values ​​of α, t is the current number of iterations, and Max_iter is the maximum number of iterations.

[0183] Step 2: Introduce an algorithm parameter a2 to calculate the parameters of the spiral shape. It changes nonlinearly with the number of iterations, rather than linearly as in the standard WOA, which helps the algorithm better balance global exploration and local development capabilities during the search process.

[0184] α 2 The formula is:

[0185]

[0186] Among them, β initial and β final They are α 2 The initial and final values ​​of .

[0187] Step 3: Introduce a dynamically adjusted algorithm parameter b to affect the shrinkage rate of the spiral shape. As the number of iterations changes, the tightness of the spiral shape changes, which helps to improve the global search capability.

[0188] The expression formula of b is:

[0189]

[0190] where b initial and b final are the initial and final values ​​of b respectively.

[0191] 4) Local Search and Evaluation

[0192] Generate candidate solutions within a certain range of the current optimal position, evaluate their fitness values, and determine whether to exit the loop. When the algorithm converges or reaches the maximum number of iterations, output the optimal diversion center position and its corresponding fitness value. Otherwise, return to the above step 2).

[0193] A local search phase is added after each main loop iteration. Local search is implemented by generating multiple candidate solutions near the leader position and evaluating these solutions. In the local search phase, a candidate solution is generated and checked to see if its fitness value is better than the current leader. If so, the leader position and score are updated, which helps the algorithm to search more carefully in a local area of ​​the search space, thereby increasing the possibility of finding the global optimal solution.

[0194] Candidate_pos=X leader +(ub-lb)*(r-0.5),

[0195] Where r represents a random number between [0, 1], ub and lb represent the upper and lower bounds of the search space, respectively.

[0196] For situations that exceed the search space boundary, the improved whale optimization algorithm will adjust its position back to the boundary. This boundary handling mechanism ensures that the algorithm always stays within the valid search space during the search process.

[0197] The position of the whale in a certain dimension is x i The lower bound of the search space in this dimension is L i , the upper bound is U i If the whale's new position x′ i If it exceeds the boundary of the search space, it needs to be adjusted. The adjusted position x″ i for:

[0198]

[0199] If the whale’s new position x′ i , in the lower bound L i , then adjust its position to the lower bound L i ; If the whale’s new position x′ i In the lower bound L i and upper bound U i (including the boundary), then keep its position unchanged; if the new position of the whale x′ i Greater than the upper bound U i , then adjust its position to the upper bound U i .

[0200] The improved whale optimization algorithm ZWOA also records the fitness value of the leader (i.e., the quality of the optimal solution) after each iteration and stores these values ​​in the convergence_curve array.

[0201] 5) Site selection decision

[0202] According to the optimal diversion center location output by the algorithm, the final site selection decision and the minimum value C are made. MIN .

[0203] The present invention proposes a diversion center site selection method that takes into account the fuel consumption of transport vehicles. Based on the existing site selection model, it fully considers the vehicle fuel consumption information under different situations, proposes a diversion center site selection model that takes into account vehicle fuel consumption, and screens out the most suitable diversion center location, thereby achieving the lowest total transportation cost of shared express boxes, alleviating the complexity of the recycling center processes, and lowering the fuel consumption of transport vehicles, effectively reducing time costs and logistics pressures.

[0204] like Figure 1 As shown, the present invention provides a method for establishing a diversion center to optimize reverse logistics transportation routes, which specifically includes obtaining the location information of express stations; in this implementation case, according to the actual situation, the latitude and longitude information of 15 specific express stations and one warehousing station in a certain area is obtained in Baidu Maps as shown in Table 1.

[0205] Table 1: Specific implementation map of each express station longitude and latitude

[0206]

[0207]

[0208] The simulation experiment data of the present invention include the following:

[0209] In this experiment, there are many constraints and management parameters, which need to be preset manually, such as the construction cost of the distribution center, the cost of transportation vehicles, the handling time, the loss rate of the shared express box during transportation, etc. The data are preset by the researchers and set to the default value. The coordinate data of each node is as follows: 118.88844,31.691516,2;

[0210] 118.8663158,31.953849,2;

[0211] 118.74873,31.883382,2;

[0212] 118.79523,31.943797,2;

[0213] 118.927347,31.910045,2;

[0214] 118.912142,31.901284,2;

[0215] 118.787558,31.774961,2;

[0216] 118.847503,31.849141,2;

[0217] 118.725652,31.637603,2;

[0218] 118.783823,31.780662,2;

[0219] 119.134461,32.225449,2;

[0220] 118.835123,32.327436,2;

[0221] 118.842206,31.964061,2;

[0222] 118.89277,31.710644,2;

[0223] 118.611232,32.063585,2;

[0224] 118.825168,31.764453,20

[0225] The present invention is implemented in matlab, according to Figure 3 The comparison chart of the improved whale optimization algorithm (ZWOA) with BWO, DBO, BOA, SCA, and WOA algorithms shows that the ZWOA algorithm is superior to these algorithms.

[0226] This paper uses the improved whale optimization algorithm (ZWOA) to select the location of the diversion center and compares the value with other algorithms. Figure 5 and Figure 3 It can be seen that the convergence speed and site selection strategy of the improved algorithm are significantly better than the traditional algorithm.

[0227] The present invention adopts an improved whale optimization algorithm, which optimizes the algorithm to a certain extent in each stage, so that the algorithm always remains in the effective search space during the search process, and can better balance the global exploration and local development capabilities during the search process, and can provide a reasonable diversion center site selection plan.

[0228] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for selecting a distribution center location considering the fuel consumption of transport vehicles, characterized in that: The method comprises the following steps: Step S1: Obtaining express station information, shared express box recycling information, vehicle operation information, and vehicle fuel consumption information under different circumstances; Step S2: Establishing a total transportation cost evaluation mechanism that takes vehicle fuel consumption into consideration, and adding a penalty mechanism to the evaluation mechanism to improve efficiency; Step S3: designing a diversion center location model that takes into account the fuel consumption of transportation vehicles by combining factors such as express station information, shared express box recycling information, vehicle operation information, and vehicle fuel consumption information under different conditions; Step S4: Based on the established diversion center location selection model, an improved whale optimization algorithm is designed to optimize the location selection method, and the total transportation cost evaluation mechanism considering vehicle fuel consumption is combined to obtain the diversion center location selection result with the optimal total cost.

2. A method for selecting a distribution center location taking into account the fuel consumption of transport vehicles according to claim 1, characterized in that: The method includes express station location information; the express station location information includes the express station geographical location information, the demand for shared express boxes at each express station, and the amount to be recycled, and the express station location information is V i =(v1,v2,v3,v4), where v1 represents longitude, v2 represents latitude, v3 represents the demand for shared express boxes, and v4 represents the amount of shared express boxes to be recycled; The shared express box recycling information includes: shared express box recycling rate, shared express box loss rate during transportation, customer shared express box loss rate, and shared express box loss rate at express stations; The vehicle operation information includes the maximum capacity of the transport vehicle, the basic rental of the vehicle, and the vehicle driving speed; Vehicle fuel consumption information for different situations includes the road fuel consumption of transport vehicles collecting and transporting shared express boxes from various express delivery stations to the distribution center, the internal transportation fuel consumption of the distribution center, and the fuel consumption when loading and unloading shared express boxes; Establish a total transportation cost evaluation mechanism that takes vehicle fuel consumption into account. The vehicle fuel consumption evaluation index is S and the evaluation mechanism set is B=(B1,B2,B3), Among them, B1 is the description of the shared express box, which is scored according to the actual situation, B2 is the freight to be paid, and B3 is the penalty for the shared express box, which is scored according to the actual situation. Let the comprehensive score set of each factor in the factor set B = (B1, B2, B3) is B = (B′1, B′2, B′3), B′ n The maximum estimated transportation cost is defined by the shared express box recycling merchants themselves, and the total transportation cost evaluation mechanism b h , b h =B′1+B′2+(B′ n -B′3) where F i represents the fuel consumption rate from the ith express station to the distribution center, D i represents the length of the transportation path from the ith express station to the distribution center, G fuel Indicates the unit price of fuel, H i represents the road condition coefficient from the ith express station to the distribution center, Q i represents the loading and unloading cost coefficient of the ith express station, Q maintenance represents the unit loading and unloading cost, L i represents the internal transportation coefficient of the i-th express station vehicle in the distribution center, L maintenance represents the internal transportation cost of the distribution center; After each transport, the diversion center will be evaluated according to the evaluation mechanism to select the route with the lowest total fuel consumption cost and ensure the stability of fuel consumption of transport vehicles.

3. The method for selecting a distribution center location considering the fuel consumption of transport vehicles according to claim 1 is characterized in that: The method is used to assist the vehicle fuel consumption evaluation mechanism, namely: S=γ×VPFCI+δ×DBFCI+μ×RCFCI+ρ×LCFCI Where S is the total score, γ, δ, μ, ρ represent the weight coefficients of each index, and their sum is 1, that is, γ+δ+μ+ρ=1, where VPFCI represents the vehicle performance fuel consumption index, and its formula is: FCR stands for fuel consumption per 100 kilometers, and its formula is: FCR' represents the fuel consumption benchmark per 100 kilometers, and EEI represents the engine efficiency index, which is used to reflect the working status of the engine. It is the ratio of the actual power of the engine to the rated power. The formula is: ω1 and ω2 are weight coefficients, set to default values ​​ω1 = 0.6, ω2 = 0.4; DBFCI stands for driving behavior fuel consumption index, and its formula is: DBFCI=ω3×(ie HAT )+ω4×(e HDT )+ω5×SDR, ω3, ω4, and ω5 are weight coefficients, which are set to default values: ω3 = 0.4, ω4 = 0.5, and ω5 = 0.

1. HAT represents the number of rapid accelerations, i.e., the number of rapid accelerations of the vehicle per unit time; HDT represents the number of rapid decelerations, i.e., the number of rapid decelerations of the vehicle per unit time; and SDR represents the smooth driving rate, which reflects the smoothness of the vehicle speed change during driving. Among them, RCFCI represents the fuel consumption index under road conditions, and its formula is: RCFCI=ω6×(1-CI)+ω7×AS ω6 and ω7 are weight coefficients, which are set to default values: ω6 = 0.4, ω7 = 0.

6. CI represents the congestion level, which is an indicator used to reflect the degree of road congestion. AS represents the average speed, which represents the average speed of the vehicle during driving. Among them, LCFCI represents the fuel consumption index under load conditions, and its formula is: T M Indicates the actual load, T' M Indicates full load, C M Indicates fuel consumption.

4. The method for selecting a distribution center location considering the fuel consumption of transport vehicles according to claim 1 is characterized in that: The diversion center site selection model must meet the following constraints, including: Condition 1: The total weight of the shared express boxes loaded on the transport vehicle cannot exceed the vehicle load, expressed as: ∑ a＝1 X a ≤X all , Condition 2: The volume of cargo loaded on the vehicle cannot exceed the vehicle capacity, expressed as: Condition 3: Must comply with local environmental laws and urban planning strategies; Condition 4: The amount of shared express boxes recycled should always be less than the capacity of the recycling center; 5. The method for selecting a distribution center location considering the fuel consumption of transport vehicles according to claim 1 is characterized in that: The method includes a diversion center location selection method model, and the objective function of the diversion center location selection method model is: minC=C1+C2+C3+C4+C5 Among them, C1 represents the basic cost, including the construction cost of the distribution center, the purchase cost of the transport vehicle, the operating cost of the distribution center, and the loss cost of the vehicle. K represents the value of the basic cost, and its value remains unchanged. The basic cost expression is as follows: Among them, C2 represents the penalty mechanism cost, including the waiting cost of the vehicle waiting for recycling at the recycling station and the delay cost of using the shared express box, that is, the delay cost of recycling the vehicle. Let p a represents the waiting cost of the recovery vehicle on site, P a represents the maximum non-penalty waiting cost in the recovery vehicle area, p b represents the delay cost of the recycling station vehicle per unit time, P b represents the maximum non-penalty delay cost in the recovery vehicle area, let t a It represents the time when the recycling station vehicle arrives at the courier station a waiting to collect the shared courier boxes to be recycled. The penalty mechanism cost is as follows: C3 is the recycling cost of shared express boxes, which includes the damage cost of shared express boxes, the recycling cost of shared express boxes, the loading and unloading cost of shared express boxes, etc. a represents the amount of shared express boxes to be recycled at express station a, L represents the loss rate of shared express boxes during the delivery process, M represents the cost of a single shared express box, and H represents the sum of the recycling cost and loading and unloading cost of the shared express box. The recycling cost expression is as follows: Among them, C4 is the transportation cost of the shared express box in the forward and reverse logistics transportation process, S a represents the distance from express station a to the shared express box distribution center, K a Z represents the amount of shared express boxes to be recycled at express station a, that is, the amount of shared express boxes to be transported at each station. a represents the demand of express delivery station a for shared express boxes that have been recycled, c a It represents the logistics cost required for the transportation of shared express boxes within a unit distance. The transportation cost expression is as follows: Where C5 is the classification cost of the shared express box, and F represents the classification time cost of a single shared express box. The classification cost is as follows: C5=K a *F.

6. The method for selecting a distribution center location considering the fuel consumption of transport vehicles according to claim 1 is characterized in that: In order to improve the problem that whales fall into local optimality in the later stage, an improved whale optimization algorithm is designed to optimize the site selection method according to the established diversion center site selection model. The improved whale optimization algorithm ZWOA is used to improve the target mathematical model to obtain the final site selection plan for the shared express box diversion center. The improved operation of the improved whale optimization algorithm ZWOA includes: adding a local search stage after each main loop iteration. The local search is achieved by generating multiple candidate solutions near the leader position and evaluating these solutions. In the local search stage, a candidate solution is generated and its fitness value is checked to see if it is better than the current leader. If so, the leader position and score are updated, which helps the algorithm to perform a more detailed search in the local area of ​​the search space, thereby increasing the possibility of finding the global optimal solution, namely: Candidate_pos=X leader +(u b -l b )*(r-0.5), Among them, r represents a random number between [0,1], u b and l b They represent the upper and lower bounds of the search space respectively.

7. The method for selecting a distribution center location considering the fuel consumption of transport vehicles according to claim 1 is characterized in that: The introduction of an adaptive step size adjustment factor makes the algorithm more flexible. The specific steps are as follows: Step 1: Introduce an algorithm parameter a, which represents the spiral shape and shrinking mechanism that affect the surrounding prey. It changes nonlinearly with the number of iterations, rather than linearly as in the standard WOA, which helps the algorithm better balance global exploration and local development capabilities during the search process. The formula for α is: Among them, α initial and α final are the initial and final values ​​of α, t is the current number of iterations, and Max_iter is the maximum number of iterations; Step 2: Introduce an algorithm parameter a2, which is used to calculate the parameters of the spiral shape. It changes nonlinearly with the number of iterations, rather than linearly as in the standard WOA, which helps the algorithm better balance global exploration and local development capabilities during the search process; The formula for α2 is: Among them, β initial and β final are the initial and final values ​​of α2 respectively; Step 3: Introduce a dynamically adjusted algorithm parameter b to affect the shrinkage rate of the spiral shape. As the number of iterations changes, the tightness of the spiral shape changes, which helps to improve the global search capability. The expression formula of b is: where b initial and b final are the initial and final values ​​of b respectively.

8. According to claim 1, a method for selecting a distribution center location considering the fuel consumption of transport vehicles, the improved whale optimization algorithm ZWOA is characterized in that: For situations that exceed the search space boundary, the improved whale optimization algorithm will adjust its position back to the boundary. This boundary processing mechanism ensures that the algorithm always stays within the valid search space during the search process. The position of the whale in a certain dimension is x i The lower bound of the search space in this dimension is L i , the upper bound is U i , if the new position of the whale is x′ i If it exceeds the boundary of the search space, it needs to be adjusted, and the adjusted position x″ i for: If the whale’s new position x′ i Less than the lower bound L i , then adjust its position to the lower bound L i ; If the whale’s new position x′ i In the lower bound L i and upper bound U i If the boundary is included, its position remains unchanged; If the whale’s new position x′ i Greater than the upper bound U i , then adjust its position to the upper bound U i ,The improved whale optimization algorithm ZWOA also records the fitness value of the leader after each iteration, i.e., the quality of the optimal solution, and stores these values ​​in the convergence_curve array, which helps to analyze the convergence performance and stability of the algorithm.

9. The method for selecting a distribution center location considering the fuel consumption of transport vehicles according to claim 1, characterized in that: The improved whale optimization algorithm is used to solve the objective function of the diversion center location selection method model, and the steps include the following: 1) Algorithm initialization and parameter definition; At the initialization stage of the algorithm, the location of each whale is set to a random value of the decision variable, which should be within the given search space, i.e., the range of possible locations; 2) Fitness assessment; For each whale position, i.e., each candidate diversion center position, the objective function is used to calculate its fitness value; 3) Whale position update; According to the principle of the whale optimization algorithm, the whale will search around the current optimal position, that is, the current optimal diversion center position, randomly select the position of other whales as a reference point, and update its own position in a spiral manner; 4) Local search and evaluation; Generate candidate solutions within a certain range of the current optimal position, evaluate their fitness values, and determine whether to exit the loop. When the algorithm converges or reaches the maximum number of iterations, output the optimal diversion center position and its corresponding fitness value, otherwise return to the above step 2); 5) Site selection decision; According to the optimal diversion center location output by the algorithm, the final site selection decision and the minimum value C are made. MIN .

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