Dual-temperature-zone-carriage-based cold-chain logistics vehicle distribution path optimization method

Abstract

This invention discloses a method for optimizing cold chain logistics vehicle delivery routes based on dual-temperature zone truck compartments, including steps S1: obtaining the coordinates and cargo demand of distribution centers and frozen / refrigerated goods delivery points; S2: determining an initial delivery route scheme consisting of fixed and variable routes based on the full truckload coefficient, less-than-truckload (LTL) demand, distance reduction coefficient, and load coefficient; S3: determining whether the variable route can be modified; if yes, proceed to S4; otherwise, the initial scheme is the optimal scheme; S4: determining the delivery route to be updated based on the remaining capacity and margin coefficient of the variable route vehicle compartments; S5: determining whether the number of vehicles required for the updated scheme is less than the number of vehicles allocated to the initial scheme; if yes, calculating the distance increase coefficient to determine the optimal scheme; otherwise, the initial scheme is the optimal scheme; S6: generating the cold chain logistics delivery route and the number of vehicles based on the optimal scheme. This invention can reduce the number of cold chain logistics vehicles and improve the utilization rate of truck compartment capacity, helping to reduce the transportation costs of enterprises.

Description

Technical Field

[0001] This invention relates to the field of cold chain logistics vehicle route planning, and more specifically to a method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments. Background Technology

[0002] In recent years, my country's cold chain logistics industry has maintained rapid market growth. The construction of national backbone cold chain logistics bases and cold chain facilities at production and sales points has steadily progressed, and the level of cold chain equipment has significantly improved. However, the construction of cold chain logistics infrastructure in rural areas of my country is insufficient. If temperature deviations occur during transportation, spoilage, deterioration, and damage from compression are easily caused. Therefore, the cost of cold chain logistics is much higher than that of ordinary express delivery, and the bottleneck problem of cold chain product delivery to villages urgently needs to be overcome.

[0003] The demand for cold chain logistics in rural my country is small in scale and scattered, making intensive transportation less feasible. Meanwhile, customer demand for cold chain products typically includes both frozen and refrigerated products, requiring separate storage and transportation in two temperature zones. To meet customer needs, traditional cold chain delivery often uses dedicated refrigerated and frozen vehicles to deliver products to the two temperature zones separately. Combined with the characteristics of rural cold chain logistics, this often leads to insufficient utilization of vehicle capacity during delivery, and the flexibility of transportation resource allocation is constrained by the type of cold chain vehicle. This inefficient transportation model results in persistently high transportation costs for cold chain logistics companies in rural areas. Summary of the Invention

[0004] The purpose of this invention is to provide a method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments, so as to overcome the shortcomings of existing technologies.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments, comprising the following steps:

[0006] S1. Data Collection: Collect the geographical coordinates of the distribution center, frozen goods distribution points, and refrigerated goods distribution points, as well as the goods demand information of the distribution points, and calculate the distance between the distribution center and each distribution point, and the distance between each distribution point;

[0007] S2. Based on the data collected in step S1, calculate the full truckload coefficient, less-than-truckload (LTL) demand, distance reduction coefficient, and load coefficient of refrigerated vehicles with dual-temperature compartments at the cargo distribution points. Determine the initial delivery routes from the distribution center as the starting point and the end point to each distribution point. The initial delivery routes are: fixed routes for full truckload demand and variable routes for LTL demand.

[0008] S3. Based on the variable routes in the initial delivery route plan obtained in step S2, determine whether there are at least two variable routes with dual-temperature compartments or variable routes where the demand is insufficient for the capacity of a single compartment of a cold chain logistics vehicle. If yes, proceed to step S4; otherwise, take the initial delivery route as the optimal plan and then proceed to step S6.

[0009] S4. Obtain the delivery route update plan based on the remaining capacity and margin coefficient of the vehicle compartments on the variable route.

[0010] S5. Determine whether the number of vehicles required for the updated delivery route is less than the number of vehicles for the initial delivery route. If yes, calculate the distance increase coefficient in the updated route to obtain the optimal route, and then proceed to step S6; otherwise, take the initial delivery route as the optimal route, and then proceed to step S6.

[0011] S6. Use the optimal solution to generate cold chain logistics delivery routes and the number of vehicles from the distribution center to each delivery point.

[0012] Furthermore, the aforementioned step S1 includes the following sub-steps:

[0013] S1.1, Geographic coordinates of the distribution center: A0, Geographic coordinates of the frozen goods distribution point: A1, A2, ..., A m Geographic coordinates of the refrigerated goods distribution point: A m+1 A m+2 A m+n ;

[0014] Collect the demand for frozen goods at frozen goods distribution points: D1, D2, ..., D m Collect data on the demand for refrigerated goods at refrigerated goods distribution points. m+1 D m+2 , ..., D m+n ;

[0015] The cold chain logistics vehicle is equipped with two dual-temperature zone compartments of equal capacity, which operate independently, and both compartments have adjustable freezing and refrigeration modes; the capacity of a single compartment of the dual-temperature zone compartment is denoted as C.

[0016] S1.2. Based on the geographical coordinates obtained in step S1.1, calculate the distance between the distribution center and each distribution point, as well as the distance between each distribution point: L ij , where, i, j∈{0, 1, 2,..., m+n}, i <j。

[0017] Furthermore, the aforementioned step S2 includes the following sub-steps:

[0018] S2.1, Delivery point A i The overall vehicle coefficient is denoted as α. iThe less-than-truckload (LTL) demand is denoted as D′. i ; D′ i =D i -2α i C,i∈{1,2,...,m+n};

[0019] S2.2. Determine the fixed route: cold chain logistics vehicles will depart from distribution center A0 based on the demand for full-vehicle transport, passing through distribution point A. i ,i∈{1,2,...,m+n},α i ≥1, and return to distribution center A0, i.e., A0→A i →A0, This fixed line requires α i A number of cold chain logistics vehicles complete point-to-point full-vehicle delivery; the initial set of delivery routes formed by the cold chain logistics vehicles required for the fixed route is denoted as P1.

[0020] The variable route is determined to be a cold chain logistics vehicle, targeting less-than-truckload (LTL) demand, departing from distribution center A0 and passing through delivery point A. j ,j∈{1,2,...,m+n},D j ′>0, and return to distribution center A0, i.e., A0→A j →A0, This variable route requires one cold chain logistics vehicle for delivery; the initial set of cold chain logistics routes required for the variable route is denoted as P2; the initial set of delivery routes from the distribution center to each delivery point is denoted as P, p∈P=P1∪P2; p is any variable route;

[0021] S2.3. Based on the initial route set in step S2.2, calculate the load factor of the cold chain logistics vehicle for each variable route with less-than-truckload (LTL) demand: the load factor of the cold chain logistics vehicle for each variable route p∈P2 with LTL demand is denoted as S. p , Among them, S p1 S is the sum of the demand for all frozen food delivery points in the variable route p; p2 This is the sum of the demand for all refrigerated delivery points in the variable route p;

[0022] S2.4 Calculate the distance reduction coefficient between every two delivery points and create a distance reduction coefficient table: The two delivery points A i A j The reduction factor between them is denoted as ΔL ij ΔL ij =L 0i +L 0j -L ij ,i,j∈{1,2,...,m+n},i <j;

[0023] S2.5 Select the maximum value in the reduction distance coefficient table and denote it as δ. If there are multiple equal maximum values, randomly select one from them. If δ>0, proceed to step S2.6. If δ=0, take the delivery route from the distribution center to each delivery point corresponding to δ=0 as the initial delivery route.

[0024] S2.6 Determine whether the less-than-truckload (LTL) demand of the two delivery points corresponding to the current δ is not 0. If yes, proceed to step S2.7. Otherwise, modify the value of the delivery point location corresponding to δ in the distance reduction coefficient table to 0, and take the delivery route from the distribution center corresponding to δ=0 to each delivery point as the initial delivery route.

[0025] S2.7 If the two delivery points corresponding to δ are not on the same delivery route, and are both connected to the delivery center in their respective delivery routes, and the delivery routes of the two delivery points meet the merging requirements, then merge the routes of the two delivery points and proceed to step S2.8; if the merging requirements are not met, then keep the delivery routes unchanged and proceed to step S2.8.

[0026] The specific route where the two delivery points are merged is as follows: the two delivery points in the combination are A... i A j The lines they are on are line p: A0→A k →…→A i →A0, Line q: A0→A j →…→A l →A0, if the two lines meet the merging requirements, the merged line will be A0→A k →…→A i →A j →…→A l →A0;

[0027] The specific requirements for merging are: the load factor of the merged line v. The merging conditions are: 1) S v1 ≤C,S v2 ≤C;2)S v1 S v2 =0, S v1 ≤2C,S v2 ≤2C; when the load factor S v When any one of the merging conditions is met, the two routes meet the merging requirements, the routes containing the two delivery points are merged, and the set of variable cold chain logistics routes P2 is updated.

[0028] S2.8. Modify the value of δ at the corresponding position in the reduction coefficient table to 0, and return to step S2.5.

[0029] Furthermore, the aforementioned step S4 includes the following sub-steps:

[0030] S4.1 Extract all delivery points from the variable routes of the dual-temperature zone carriages or the variable routes where the demand is insufficient for the capacity of a single carriage of the cold chain logistics vehicle, and form a set of dual-temperature co-distribution delivery points denoted as R. Denote the remaining variable route set in the variable route set P2 as P′2.

[0031] S4.2 Calculate the remaining cargo capacity of cold chain logistics vehicles in the variable route set P′2; the remaining cargo capacity of cold chain logistics vehicles on route v is denoted as T. v , Among them, T v1 T represents the remaining capacity of the refrigerated carriages in line v; v2 This represents the remaining capacity of refrigerated carriages in route v; if route v includes both frozen and refrigerated delivery point needs, If route V only includes demand for refrigerated delivery points and there are no spare carriages. If route V only includes the demand for refrigerated delivery points and there are no spare carriages. If route V only includes demand for refrigerated delivery points and one carriage is idle. If route V only includes the demand for refrigerated delivery points and one carriage is idle.

[0032] S4.3, Randomly select a delivery point A from R. i Calculate A i The margin coefficient allocated to all variable lines in P′2;

[0033] The margin coefficient of line v is denoted as O. v If A i For frozen food delivery points, O v =T v1 -D′ i If A i For refrigerated delivery points, O v =T v2 -D′ i ;

[0034] S4.4, Determine all O v Are all less than 0? If so, then use A. i Create a new variable route for the first delivery point and assign it to P′2; otherwise, in O v Select the variable line corresponding to the minimum value among all values ​​≥0, and set A... i Assign it to the variable line corresponding to the minimum value;

[0035] S4.5, Delete A from R i Update the variable route, remaining capacity, and carriage type. Then return to step S4.3; otherwise, obtain the delivery route update plan, and denote the set of delivery routes as follows.

[0036] Further, in the aforementioned step S5, obtaining the optimal route plan specifically includes the following sub-steps:

[0037] S5.1. Select a route in P'2 for which the delivery order has not been determined. Based on all the delivery points on this route, form an initial route by connecting the distribution center with any one of the delivery points;

[0038] S5.2. Randomly select a delivery point not on the route as an insertion point, and calculate the distance increment coefficients for inserting it into all insertable positions respectively;

[0039] The distance increment coefficient is denoted as ΔL'; ij ; ΔL' ij = L ik + L jk - L ij , where i, j ∈ {0, 1, 2,..., m + n}, i < j; k ∈ {1, 2,..., m + n}, k ≠ i, j; where A i is the front-end node of the insertion position, A j is the back-end node of the insertion position, and A k is the insertion point;

[0040] S5.3. Select the insertion position with the minimum distance increment coefficient, insert the selected delivery point into this position. If there are multiple insertion positions with equal and minimum distance increment coefficients, randomly insert the selected delivery point into one of them; update the route, and then return to execute step S5.2 until all delivery points are inserted into the route; The insertion into the route is specifically:

[0041] The insertion position with the minimum distance increment coefficient is A i → A j , the insertion point is A k , and the new route after insertion into the route is A0 → … → A i → A k → A j → … → A0;

[0042] S5.4. Determine whether all routes in P'2 have been selected; if so, obtain the final variable route delivery path, which together with the fixed route set P1 in the initial delivery route plan forms the optimal plan.

[0043] Compared to existing technologies, the beneficial effects of this invention are as follows: The cold chain logistics vehicle delivery route optimization method based on dual-temperature zone compartments provided by this invention offers greater flexibility in the allocation of transportation resources compared to single-temperature zone vehicles. It can reduce the number of cold chain delivery vehicles while increasing the utilization rate of vehicle capacity, making it more suitable for cold chain logistics delivery scenarios in rural areas with small-scale and scattered cold chain logistics demands, and effectively reducing the transportation costs of cold chain logistics companies. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of a route optimization method for cold chain logistics vehicles based on dual-temperature zone compartments.

[0045] Figure 2 This is a schematic diagram showing the locations of the distribution center and delivery points in the example.

[0046] Figure 3 This is a schematic diagram of the optimal delivery route scheme in the example. Detailed Implementation

[0047] To better understand the technical content of the present invention, specific embodiments are described below in conjunction with the accompanying drawings.

[0048] In this invention, various aspects of the invention are described with reference to the accompanying drawings, in which numerous illustrative embodiments are shown. Embodiments of the invention are not limited to those depicted in the drawings. It should be understood that the invention is implemented through any of the various concepts and embodiments described above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed herein are not limited to any particular implementation. Furthermore, some aspects of the invention disclosed may be used alone or in any suitable combination with other aspects of the invention disclosed.

[0049] like Figure 1 As shown, the present invention provides a method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments, comprising the following steps: S1, Data Collection: Collecting the geographical coordinates of the distribution center, frozen goods delivery points, and refrigerated goods delivery points, as well as the goods demand information of the delivery points, and creating a table of goods demand at the delivery points, as shown in Table 1; calculating the distance between the distribution center and each delivery point, and the distance between each delivery point; Step S1 includes the following steps S1.1 to S1.2:

[0050] The cold chain logistics vehicle is equipped with two dual-temperature zone compartments of equal capacity, which operate independently, and both compartments have adjustable freezing and refrigeration modes; the capacity of a single compartment of the dual-temperature zone compartment is denoted as C.

[0051] S1.1, Geographic coordinates of the distribution center: A0, Geographic coordinates of the frozen goods distribution point: A1, A2, ..., Am Geographic coordinates of the refrigerated goods distribution point: A m+1 A m+2 A m+n ;

[0052] Collect the demand for frozen goods at frozen goods distribution points: D1, D2, ..., D m Collect data on the demand for refrigerated goods at refrigerated goods distribution points. m+1 D m+2 , ..., D m+n ;

[0053] S1.2. Based on the geographical coordinates obtained in step S1.1, calculate the distances between the distribution center and each distribution point, as well as the distances between each distribution point, to create a cold chain logistics vehicle transportation distance matrix, as shown in Table 2. The transportation distance is L. ij , where, i, j∈{0, 1, 2,..., m+n}, i <j。

[0054] Table 1

[0055] node x / km y / km D / kg <![CDATA[A0]]> 0 0 <![CDATA[A1]]> -3.8 4.16 3100 <![CDATA[A2]]> 4.9 7.86 12300 <![CDATA[A3]]> -7.27 -5.86 1600 <![CDATA[A4]]> -0.29 -9.4 1100 <![CDATA[A5]]> 3.16 -4.43 1000 <![CDATA[A6]]> 0.36 -9.52 900 <![CDATA[A7]]> -4.27 -1.7 2700 <![CDATA[A8]]> -6.81 -1.19 1800 <![CDATA[A9]]> -3.21 5.61 6200 <![CDATA[A 10 ]]> 8.51 -2.24 800 <![CDATA[A 11 ]]> 7.56 3.45 500

[0056] In this system, node 0 is the distribution center, and nodes 1, 2, ..., 11 are 11 distribution points, denoted as A0, A1, ..., A2, ..., A3, respectively. 11 A Cartesian coordinate system is established with the distribution center as the origin and due north as the positive y-axis; x represents the x-coordinates of the 12 nodes, denoted as x0, x1, ..., x2. 11 ; y represents the ordinates of the 12 nodes, denoted as y0, y1, ..., y2. 11 The demand for frozen goods at the 6 frozen food distribution points is denoted as D1, D2, ..., D6; the demand for refrigerated goods at the 5 distribution points is denoted as D7, D8, ..., D6. 11 ;like Figure 2 As shown;

[0057] Table 2

[0058]

[0059] In a specific implementation, the transport distance matrix uses Euclidean distance, i.e. S2. Based on the data collected in step S1, calculate the full truckload coefficient, less-than-truckload (LTL) demand, distance reduction coefficient, and load coefficient of refrigerated vehicles with dual-temperature compartments at the cargo distribution points. Determine the initial delivery routes from the distribution center as the starting point and the end point to each distribution point. The initial delivery routes are: fixed routes for full truckload demand and variable routes for LTL demand.

[0060] The cold chain logistics vehicle is equipped with two dual-temperature compartments of equal capacity, which operate independently, and both compartments have adjustable freezing and refrigeration modes; the capacity of a single compartment of the dual-temperature compartment is denoted as C = 2500 kg.

[0061] S2.1, Delivery point A i The overall vehicle coefficient is denoted as α. i The less-than-truckload (LTL) demand is denoted as D′. i ; D′ i =D i -2α i C, i∈{1,2,...,m+n}; Update the goods demand information of the distribution points as shown in Table 3.

[0062] Table 3

[0063] node x / km y / km D / kg α D' / kg <![CDATA[A0]]> 0 0 <![CDATA[A1]]> -3.8 4.16 3100 0 3100 <![CDATA[A2]]> 4.9 7.86 12300 2 2300 <![CDATA[A3]]> -7.27 -5.86 1600 0 1600 <![CDATA[A4]]> -0.29 -9.4 1100 0 1100 <![CDATA[A5]]> 3.16 -4.43 1000 0 1000 <![CDATA[A6]]> 0.36 -9.52 900 0 900 <![CDATA[A7]]> -4.27 -1.7 2700 0 2700 <![CDATA[A8]]> -6.81 -1.19 1800 0 1800 <![CDATA[A9]]> -3.21 5.61 6200 1 1200 <![CDATA[A 10 ]]> 8.51 -2.24 800 0 800 <![CDATA[A 11 ]]> 7.56 3.45 500 0 500

[0064] S2.2. Determine the fixed route: cold chain logistics vehicles will depart from distribution center A0 based on the demand for full-vehicle transport, passing through distribution point A. i ,i∈{1,2,...,m+n},α i ≥1, and return to distribution center A0, i.e., A0→A i →A0, This fixed line requires α i A number of cold chain logistics vehicles complete point-to-point full-vehicle delivery; the initial set of delivery routes formed by the cold chain logistics vehicles required for the fixed route is denoted as P1.

[0065] The variable route is determined to be a cold chain logistics vehicle, targeting less-than-truckload (LTL) demand, departing from distribution center A0 and passing through delivery point A. j ,j∈{1,2,...,m+n},D′ j >0, and return to distribution center A0, i.e., A0→A j →A0, This variable route requires one cold chain logistics vehicle for delivery; the initial set of cold chain logistics routes required for the variable route is denoted as P2; the initial set of delivery routes from the distribution center to each delivery point is denoted as P, p∈P=P1∪P2; p is any variable route;

[0066] Fixed route 1 is A0→A2→A0, which requires 2 cold chain logistics vehicles for delivery; fixed route 2 is A0→A9→A0, which requires 1 cold chain logistics vehicle for delivery.

[0067] Variable route 1 is A0→A1→A0; Variable route 2 is A0→A2→A0; Variable route 3 is A0→A3→A0; Variable route 4 is A0→A4→A0; Variable route 5 is A0→A5→A0; Variable route 6 is A0→A6→A0; Variable route 7 is A0→A7→A0; Variable route 8 is A0→A8→A0; Variable route 9 is A0→A9→A0; Variable route 10 is A0→A 10 →A0; Variable line 11 is A0→A 11 →A0; Each requires one refrigerated logistics vehicle for delivery;

[0068] S2.3. Based on the initial route set in step S2.2, calculate the load factor of the cold chain logistics vehicle for each variable route with less-than-truckload (LTL) demand: the load factor of the cold chain logistics vehicle for each variable route p∈P2 with LTL demand is denoted as S. p , Among them, S p1 S is the sum of the demand for all frozen food delivery points in the variable route p; p2 This is the sum of the demand for all refrigerated delivery points in the variable route p;

[0069]

[0070] S2.4 Calculate the reduction distance coefficient between every two delivery points and create a reduction distance coefficient table, as shown in Table 4. The two delivery points A... i A j The reduction factor between them is denoted as ΔL ij ΔL ij =L 0i +L 0j -L ij ,i,j∈{1,2,...,m+n},i <j;

[0071] Table 4

[0072]

[0073] S2.5 Select the maximum value in the reduction distance coefficient table and denote it as δ. If there are multiple equal maximum values, randomly select one from them. If δ>0, proceed to step S2.6. If δ=0, take the delivery route from the distribution center to each delivery point corresponding to δ=0 as the initial delivery route.

[0074] S2.6 Determine whether the less-than-truckload (LTL) demand of the two delivery points corresponding to the current δ is not 0. If yes, proceed to step S2.7. Otherwise, modify the value of the delivery point location corresponding to δ in the distance reduction coefficient table to 0, and take the delivery route from the distribution center corresponding to δ=0 to each delivery point as the initial delivery route.

[0075] S2.7 If the two delivery points corresponding to δ are not on the same delivery route, and are both connected to the delivery center in their respective delivery routes, and the delivery routes of the two delivery points meet the merging requirements, then merge the routes of the two delivery points and proceed to step S2.8; if the merging requirements are not met, then keep the delivery routes unchanged and proceed to step S2.8.

[0076] The specific route where the two delivery points are merged is as follows: the two delivery points in the combination are A... i A j The lines they are on are line p: A0→A k →…→A i →A0, Line q: A0→A j →…→A l →A0, if the two lines meet the merging requirements, the merged line will be A0→A k →…→A i →A j →…→A l →A0;

[0077] The specific requirements for merging are: the load factor of the merged line v. The merging conditions are: 1) S v1 ≤C,S v2 ≤C;2)S v1 S v2 =0, S v1 ≤2C,S v2 ≤2C; when the load factor S v When any one of the merging conditions is met, the two routes meet the merging requirements, the routes containing the two delivery points are merged, and the set of variable cold chain logistics routes P2 is updated.

[0078] A2, A 11 The two delivery points are not on the same route, and both are connected to the distribution center on their respective routes; the load factor of the merged route is equal to The merging condition 1 is met; the merged route is A0→A2→A 11 →A0;

[0079] S2.8, Modify the value of δ at the corresponding position in the reduction coefficient table to 0, and return to step S2.5;

[0080] In the reduction coefficient table, change the value of δ (18.27) to 0, update the reduction coefficient table, and return to step S2.5; the maximum value in the reduction coefficient table is δ = 12.42, corresponding to two delivery points A2 and A3 respectively. 11 ;

[0081] A2, A 11 Since the less-than-truckload (LTL) demand is not zero, proceed to step 2.7;

[0082] A2, A 11 The two delivery points are not on the same route, and both are connected to the distribution center on their respective routes; the load factor of the merged route is equal to The merging condition 1 is met; the merged route is A0→A2→A 11 →A0;

[0083] In the reduction coefficient table, change the value of δ at the corresponding position from 12.42 to 0, update the reduction coefficient table, and return to step S2.5;

[0084] Following this logic, when δ = 0 is selected in step 2.5, the variable route delivery scheme P2 for less-than-truckload (LTL) demand is obtained as follows:

[0085] Variable Route 1 has a delivery path of A0→A4→A6→A5→A0, with a frozen goods carrying capacity of 3000kg; Variable Route 2 has a delivery path of A0→A9→A2→A 11 →A 10 →A0; Frozen goods carrying capacity is 2300kg, refrigerated goods carrying capacity is 2500kg; Variable Route 3 delivery path is A0→A3→A8→A A The carrying capacity for frozen goods is 1600kg, and the carrying capacity for refrigerated goods is 1700kg; the delivery route of Variable Route 4 is A0→A1→A0, and the carrying capacity for frozen goods is 3100kg; the delivery route of Variable Route 5 is A0→A7→A0, and the carrying capacity for refrigerated goods is 2700kg.

[0086] For the demand of whole vehicles, the fixed route delivery plan P1 is as follows: Fixed route 1 is A0→A2→A0, which requires 2 cold chain logistics vehicles for delivery; Fixed route 2 is A0→A9→A0, which requires 1 cold chain logistics vehicle for delivery; The initial delivery route plan from the distribution center to each delivery point is P=P1∪P2;

[0087] S3. Based on the variable routes in the initial delivery route plan obtained in step S2, determine whether there are at least two variable routes with dual-temperature compartments or variable routes where the demand is insufficient for the capacity of a single compartment of a cold chain logistics vehicle. If so, proceed to step S4. Obtain the delivery route update plan based on the remaining capacity and margin coefficient of the vehicle compartments on the variable routes.

[0088] The dual-temperature zone carriage refers to a carriage that simultaneously accommodates the needs of both frozen and refrigerated delivery points. The insufficient demand in a single carriage of a cold chain logistics vehicle refers to a situation where another carriage of the vehicle is temporarily idle.

[0089] In a specific implementation, the initial delivery route plan includes two dual-temperature zone variable car routes, variable route 2 and variable route 3, and step S4 is executed.

[0090] S4. Based on the remaining capacity and margin coefficient of the vehicles on the variable route, the delivery route is the plan to be updated.

[0091] S4.1 Extract all delivery points from the variable routes of the dual-temperature zone carriages or the variable routes where the demand is insufficient for the capacity of a single carriage of the cold chain logistics vehicle, and form a set of dual-temperature co-distribution delivery points denoted as R. Denote the remaining variable route set in the variable route set P2 as P′2.

[0092] Extract all delivery points from variable routes 2 and 3, forming a set of dual-temperature co-delivery delivery points denoted as R, where R = {A2, A3, A8, A9, A...} 10 A 11 The set of remaining variable lines in the variable line set P2 is denoted as P′2, which includes line 1, line 4, and line 5.

[0093] S4.2 Calculate the remaining cargo capacity of cold chain logistics vehicles in the variable route set P′2; the remaining cargo capacity of cold chain logistics vehicles on route v is denoted as T. v , Among them, T v1 T represents the remaining capacity of the refrigerated carriages in line v; v2 This represents the remaining capacity of refrigerated carriages in route v; if route v includes both frozen and refrigerated delivery point needs, If route V only includes demand for refrigerated delivery points and there are no spare carriages. If route V only includes the demand for refrigerated delivery points and there are no spare carriages. If route V only includes demand for refrigerated delivery points and one carriage is idle. If route V only includes the demand for refrigerated delivery points and one carriage is idle. Remaining cargo capacity of refrigerated logistics vehicles on Variable Route 1 Remaining cargo capacity of refrigerated logistics vehicles on Variable Route 4 Remaining cargo capacity of refrigerated logistics vehicles on Route 5

[0094] S4.3, Randomly select a delivery point A from R. i Calculate A i The margin coefficient allocated to all variable lines in P′2;

[0095] The margin coefficient of line v is denoted as O. v If A i For frozen food delivery points, O v =T v1 -D′ i If A i For refrigerated delivery points, O v =T v2-D′ i ; Randomly select A3, D′3 = 1600 kg; O1 = 400 kg, O4 = 300 kg, O5 = -1600 kg;

[0096] S4.4. Determine whether all O v are less than 0. If so, create a new variable route with A i as the first delivery point and include it in P′2; otherwise, select the variable route corresponding to the minimum value among all values of O[[ID=)) v ≥0, and assign A i to the variable route corresponding to this minimum value; Since O1, O4 ≥ 0 and O4 < O1, A3 is assigned to variable route 4;

[0097] S4.5. Delete A i from R, update the variable routes, remaining capacities, and car body types. If then return to step 4.3; otherwise, obtain the delivery route to be updated plan, and record the delivery route set as

[0098] Delete A3 from R and update Return to step S4.3;

[0099] Randomly select A2, D′2 = 2300 kg; O1 = -300 kg, O4 = -2000 kg, O5 = -230 kg;

[0100] O1, O4, O5 < 0; Therefore, create a new variable route 6 with A2 as the first delivery point and include it in P′2;

[0101] [[ID=)%]]Delete A2 from R and update Return to step S4.3;

[0102] And so on. When executing step 3.5 is reached, obtain the delivery route to be updated plan;

[0103] Variable route 1 includes A4, A5, A6, and the refrigerated cargo carrying capacity is 3000 kg; Variable route 2 includes A2, A9, A 10 , A 11 , and the refrigerated cargo carrying capacity is 2300 kg, and the chilled cargo carrying capacity is 2500 kg; Variable route 3 includes A7, A8, and the chilled cargo carrying capacity is 4500 kg; Variable route 4 includes A1, A3, and the refrigerated cargo carrying capacity is 4700 kg. S5. Determine whether the number of vehicles required for the delivery route to be updated plan is less than the number of vehicles in the initial delivery route. If so, calculate the distance increase coefficient in the to-be-updated plan to obtain the optimal route plan Then execute step S6; otherwise, use the initial route as the optimal route plan P* = P, and then step S6 is executed.

[0104] If the new distribution route plan has 4 variable routes and the initial distribution route plan has 5 variable routes, then the optimal route plan For each variable route in the distribution route to be updated plan Determine the distribution order of each distribution point to obtain the optimal variable route plan, specifically as follows:

[0105] S5.1. Select a route in P′2 whose distribution order has not been determined. Based on all the distribution points on this route, form an initial route between the distribution center and any one of the distribution points; Select variable route 1, and the initial route is A0→A6→A0.

[0106] S5.2. Randomly select a distribution point not on the route as the insertion point, and calculate the increased distance coefficient for inserting it into all insertable positions respectively;

[0107] The increased distance coefficient is denoted as ΔL′ ij ; ΔL′ ij = L ik + L jk - L ij , i, j ∈ {0, 1, 2,..., m + n}, i < j; k ∈ {1, 2,..., m + n}, k ≠ i, j; where, A i is the front-end node of the insertion position, A j is the back-end node of the insertion position, A k is the insertion point; Select A4 as the insertion point, and the insertion positions are A0→A6 and A6→A0, and the increased distance coefficients are both 0.539.

[0108] S5.3. Select the insertion position with the smallest increased distance coefficient, insert the selected distribution point into this position. If there are multiple insertion positions with equal and smallest increased distance coefficients, randomly insert the selected distribution point into one of them; Update the route, and then return to execute step S5.2 until all distribution points are inserted into the route; The insertion into the route is specifically:

[0109] The insertion position with the smallest increased distance coefficient is A i →A j , the insertion point is A k , and the new route after insertion into the route is A0→…→A i →A k →A j →…→A0;

[0110] Insert A4 into A0→A6 to get the new route A0→A4→A6→A0, and return to step 5.2; ​Selecting A5 as the insertion point, the insertion positions are A0→A4, A4→A6 and A6→A0, with increment coefficients of 2.087, 11.2 and 1.724 respectively;

[0112] Insert A5 into A6→A0 to obtain the new line A0→A4→A6→A5→A0;

[0113] S5.4 Determine whether all routes of P′2 have been selected; if so, the final variable route delivery path is obtained, which together with the fixed route set P1 in the initial delivery route plan constitutes the optimal solution.

[0114] Variable Route 1 delivery path is A0→A4→A6→A5→A0; Variable Route 2 delivery path is A0→A9→A2→A 11 →A 10 →A0; the delivery route for variable route 3 is A0→A7→A8→A0; the delivery route for variable route 4 is A0→A1→A3→A0.

[0115] S6. Use the optimal solution to generate cold chain logistics delivery routes and the number of vehicles from the distribution center to each delivery point.

[0116] In a specific implementation, the optimal delivery route scheme is as follows: Figure 3 As shown in Table 5;

[0117] Table 5

[0118]

[0119] While the present invention has been described above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A method for optimizing delivery routes for cold chain logistics vehicles based on dual-temperature zone compartments, characterized in that, Includes the following steps: S1. Data Collection: Collect the geographical coordinates of the distribution center, frozen goods distribution points, and refrigerated goods distribution points, as well as the goods demand information of the distribution points, and calculate the distance between the distribution center and each distribution point, and the distance between each distribution point; S2. Based on the data collected in step S1, calculate the full truckload coefficient, less-than-truckload (LTL) demand, distance reduction coefficient, and load coefficient of refrigerated vehicles with dual-temperature compartments at the cargo distribution points. Determine the initial delivery routes from the distribution center as the starting point and the end point to each distribution point. The initial delivery routes are: fixed routes for full truckload demand and variable routes for LTL demand. S3. Based on the variable routes in the initial delivery route plan obtained in step S2, determine whether there are at least two variable routes with dual-temperature compartments or variable routes where the demand is insufficient for the capacity of a single compartment of a cold chain logistics vehicle. If yes, proceed to step S4; otherwise, take the initial delivery route as the optimal plan and then proceed to step S6. S4. Obtain the delivery route update plan based on the remaining capacity and margin coefficient of the vehicles on the variable route; specifically including the following sub-steps: S4.1 Extract all delivery points on variable routes of dual-temperature zone wagons or variable routes where demand is insufficient for the capacity of a single wagon compartment in a cold chain logistics vehicle, and form a set of dual-temperature co-distribution delivery points, denoted as . , to change the set of lines The set of remaining variable lines is denoted as ; S4.2 Calculate the set of variable routes Remaining cargo space in cold chain logistics vehicles; routes The remaining capacity of the cargo compartment of a cold chain logistics vehicle is recorded as follows: , ;in, For the line Remaining capacity of the medium- and refrigerated car compartments; For the line Remaining capacity of the refrigerated carriages; if the line It includes both frozen and refrigerated delivery point needs. If the line It only includes the needs of frozen food delivery points and has no idle truck compartments. If the line It only includes the needs of refrigerated delivery points and has no idle truck compartments. If the line It only includes the needs of frozen food delivery points and has one spare carriage. If the line It only includes the needs of refrigerated delivery points and has one spare carriage. ; S4.3 Random sampling One of the delivery points , calculation will Assigned to The margin coefficient for all variable lines in the system; The line The margin coefficient is denoted as ,like It is a frozen food delivery point. ;like It is a refrigerated delivery point. , Indicates less-than-truckload (LTL) demand; S4.4, Determine all Are all less than 0? If so, then... Create a new variable route for the first delivery point and assign it to [the relevant area]. In the middle; otherwise in Select the variable line corresponding to the minimum value from all values, and... Assign it to the variable line corresponding to the minimum value; S4.5, from Delete Update the variable route, remaining capacity, and carriage type. If the condition is met, return to step S4.3; otherwise, obtain the delivery route update plan. The set of delivery routes is denoted as... ; S5. Determine whether the number of vehicles required for the updated delivery route is less than the number of vehicles for the initial delivery route. If yes, calculate the distance increase coefficient in the updated route to obtain the optimal route, and then proceed to step S6; otherwise, take the initial delivery route as the optimal route, and then proceed to step S6. S6. Use the optimal solution to generate cold chain logistics delivery routes and the number of vehicles from the distribution center to each delivery point.

2. The method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments according to claim 1, characterized in that, Step S1 includes the following sub-steps: S1.1, Collect the geographical coordinates of the distribution center: Geographic coordinates of the frozen goods distribution point: Geographic coordinates of the refrigerated goods distribution point: ; Collect information on the demand for frozen goods at frozen goods distribution points: Collect information on the demand for refrigerated goods at refrigerated goods distribution points. ; The cold chain logistics vehicle is equipped with two dual-temperature zone compartments of equal capacity, which operate independently, and both compartments have adjustable freezing and refrigeration modes; the capacity of a single compartment of the dual-temperature zone vehicle is denoted as C. S1.

2. Based on the geographical coordinates obtained in step S1.1, calculate the distance between the distribution center and each distribution point, as well as the distance between each distribution point: ,in, .

3. The method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments according to claim 2, characterized in that, Step S2 includes the following sub-steps: S2.1, Delivery point The overall vehicle coefficient is denoted as Less-than-truckload (LTL) demand is recorded as ; ; S2.2, Determine fixed routes for cold chain logistics vehicles based on full vehicle demand from the distribution center. Departure, passing through delivery points and returned to the distribution center. ,Right now This fixed line needs A number of cold chain logistics vehicles complete point-to-point full-vehicle delivery; the initial set of delivery routes formed by the cold chain logistics vehicles required for the fixed routes is denoted as . ; The variable route was determined to be a cold chain logistics vehicle for less-than-truckload (LTL) demand from the distribution center. Departure, passing through delivery points and returned to the distribution center. ,Right now This variable route requires one refrigerated logistics vehicle for delivery; the initial set of refrigerated logistics routes required for the variable route is denoted as . The initial set of delivery routes from the distribution center to each delivery point is denoted as . , ; For any variable line; S2.

3. Based on the initial route set from step S2.2, calculate the load factor for each variable route cold chain logistics vehicle for less-than-truckload (LTL) demand: the variable route The load factor for cold chain logistics vehicles targeting less-than-truckload (LTL) demand is denoted as: , ,in, For variable lines The sum of demand from all frozen food delivery points in the region; For variable lines The sum of demand from all refrigerated delivery points in the region; S2.4 Calculate the reduction distance coefficient between every two delivery points and create a reduction distance coefficient table: the two delivery points The difference factor between them is denoted as , ; S2.

5. Select the maximum value from the reduction coefficient table, and denote it as... If there are multiple equal maximum values, then one is randomly selected from them; if Execute step S2.6, if Then, based on that The delivery routes from the corresponding distribution center to each delivery point are the initial delivery routes; S2.6, Determine the current situation If the less-than-truckload (LTL) demand at both delivery points is not zero, proceed to step S2.7; otherwise, check the distance reduction coefficient table. The value corresponding to the delivery point location is changed to 0, and this is used as the basis for further changes. The delivery routes from the corresponding distribution center to each delivery point are the initial delivery routes; S2.7, if If the two corresponding delivery points are not on the same delivery route, and both are connected to the distribution center on their respective delivery routes, and the delivery routes of the two delivery points meet the merging requirements, then merge the routes of the two delivery points and proceed to step S2.8; if the merging requirements are not met, then keep the delivery routes unchanged and proceed to step S2.

8. The specific routes where the two delivery points are merged are as follows: the two delivery points in the combination are respectively... The lines they are located on are respectively the lines : ,line : If the two lines meet the requirements for merging, the merged line will be... ; The specific requirements for merging are: the merged lines load factor The conditions for merging are: 1) ;2) When the load factor When any one of the merging conditions is met, the two routes meet the merging requirements, the routes containing the two delivery points are merged, and the set of variable routes for cold chain logistics is updated. ; S2.8, In the reduction coefficient table, Change the value at the corresponding position to 0 and return to step S2.

5.

4. The method for optimizing the delivery route of cold chain logistics vehicles based on dual-temperature zone compartments according to claim 3, characterized in that... Step S5, obtaining the optimal route plan specifically includes the following sub-steps: S5.1, Select For a route with an undetermined delivery order, the distribution center is paired with any one of the delivery points on that route to form an initial route. S5.2 Randomly select a delivery point that is not on the route as the insertion point, and calculate the distance increase coefficient for inserting it into all possible insertion positions; The distance extension factor is denoted as ; ;in, To insert the front node, To insert the backend node, The insertion point; S5.3 Select the insertion position with the smallest distance increment coefficient and insert the selected delivery point into this position. If multiple insertion positions have the same and smallest distance increment coefficient, randomly insert the selected delivery point into one of them; update the route, and then return to step S5.2 until all delivery points have been inserted into the route; the insertion into the route specifically means: The insertion position with the smallest increment factor is The insertion point is After being inserted into the line, the new line is ; S5.4 Determine whether a selection has been made. All routes; if so, obtain the final variable route delivery path, and compare it with the set of fixed routes in the initial delivery route plan. This constitutes the optimal solution.

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