A logistics yard vehicle batch scheduling method and system considering multiple picking locations

Abstract

The present application relates to a kind of logistics park vehicle batching scheduling method considering multiple pick-up location, comprising the following steps: step S1: the operation characteristics of the multiple pick-up location vehicle of logistics park are obtained, and vehicle operation model is constructed;Step S2: based on vehicle operation model, with the operation time after batching minimization as objective function, vehicle batching scheduling optimization model is constructed;Step S3: based on vehicle batching scheduling optimization model, according to heuristic algorithm, the optimal vehicle batching scheme and corresponding scheduling plan are solved.The present application avoids the irrationality of artificial scheduling, optimizes the operation process of vehicle, improves the efficiency of operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle scheduling, in particular to a logistics park vehicle batch scheduling method and system considering multiple pick-up locations. BACKGROUND

[0002] In the traditional logistics park logistics scheduling system, the time of vehicle arriving at the logistics park follows the principle of first-come-first-served, and after the vehicle arrives at the site, the logistics park staff schedules the vehicle arriving at the site by manual operation. With the development of logistics in China, the operation volume of the logistics park is increasing, and the daily vehicle throughput is also rising. If the time of vehicle arriving at the logistics park is not reasonably allocated, a large number of vehicles may arrive at the logistics park at the same time. Since the entrance space of the logistics park is limited, the operation time of the un-planned vehicle will cause congestion at the entrance of the logistics park, leading to disorderly operation and increasing the operating cost of the enterprise. Therefore, it is necessary to realize the batch arrival operation of the vehicle, optimize the arrival time of the vehicle, and improve the efficiency of vehicle scheduling. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a logistics park vehicle batch scheduling method and system considering multiple pick-up locations, which effectively improves the efficiency of vehicle scheduling.

[0004] To achieve the above purpose, the present application adopts the following technical solutions:

[0005] A logistics park vehicle batch scheduling method considering multiple pick-up locations, comprising the following steps:

[0006] Step S1: obtaining the operation characteristics of the logistics park multiple pick-up location vehicle, and constructing a vehicle operation model taking the vehicle pick-up data and the logistics park yard cargo placement data as input and the vehicle pick-up operation scheduling plan as output;

[0007] Step S2: based on the vehicle operation model, constructing a vehicle batch scheduling optimization model with the minimum batch operation time as the objective function;

[0008] Step S3: based on the vehicle batch scheduling optimization model, solving the optimal vehicle batch scheme and the corresponding scheduling plan according to the heuristic algorithm.

[0009] Further, the vehicle batch scheduling optimization model is specifically:

[0010] The objective function is:

[0011]

[0012] The constraint condition is:

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[0018]

[0019]

[0020]

[0021]

[0022]

[0023]

[0024] l, h∈I, j∈J, k∈K, U jk ∈1,2,...|U jk |

[0025]

[0026] i∈I, r, m∈J, k∈K, w ik ∈1,2,...|W ik |

[0027]

[0028] Where I is the vehicle set, J is the pickup location set, K is the batch set, NI is the total number of vehicles in operation, and G... i T represents the number of pickup locations for vehicle i. k For the operation time of the kth batch of vehicles, u jk w represents the position of the vehicle in the picking position j of the kth batch in the work sequence. ik Let U be the position of the pickup location of the kth batch in the operation sequence of vehicle i. jk For the yard assembly of the kth batch of pickup location j, |U jk |W represents the number of vehicles operating at pickup location j in the kth batch. ik | represents the number of pickup locations for vehicle i in the kth batch of operations. Let be the start time of the operation for vehicle i at pickup location j in the kth batch. Let T be the start time of the operation for vehicle i at pickup location j in the kth batch. ijkLet M be the operation time of vehicle i at pickup location j in the kth batch, and let M be a number greater than a preset value. ik Z takes the value 1 if vehicle i belongs to the kth batch, and 0 otherwise. ijk If vehicle i belongs to the k-th batch and is operating at pickup location j, the value is 1; otherwise, the value is 0. If vehicle i belongs to the kth batch and is the uth in the operation sequence of pickup location j jk If the position is specified, the value is 1; otherwise, the value is 0. If the pickup location j of the kth batch is the wth position in the operation sequence of vehicle i... ik If the position is specified, the value is 1; otherwise, the value is 0.

[0029] Furthermore, step S3 specifically includes:

[0030] (1) Divide a single vehicle into a batch, calculate the idle rate after merging batches, and select the merged batch with the smallest idle rate as a new batch.

[0031] (2) Add the new merged batch to the original batch, continue to calculate the idle rate after merging batches, and select the merged batch with the smallest idle rate as a new batch.

[0032] (3) If the operation time of the new batch after merging the two batches exceeds the maximum operation time of each batch, then the idle rate after merging the two batches is defined as infinite.

[0033] (4) Repeat the above merging steps until the idle rate after merging any batch is infinite, then stop the merging process and obtain the final vehicle batching result.

[0034] A system for a batch scheduling method for logistics park vehicles considering multiple pickup locations includes a processor, a memory, and a computer program stored in the memory. When the processor executes the computer program, it specifically performs the steps in the batch scheduling method for logistics park vehicles considering multiple pickup locations as described above.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] 1. This invention can improve the time and space utilization of logistics parks and rationally divide the work vehicles into batches;

[0037] 2. This invention aims to minimize vehicle operation time, avoid the inefficiencies of manual scheduling, optimize the vehicle operation process, and improve operation efficiency. Attached Figure Description

[0038] Figure 1 This is a flowchart of the method of the present invention;

[0039] Figure 2 This is a schematic diagram of a heuristic algorithm for solving a vehicle batch scheduling model in one embodiment of the present invention. Detailed Implementation

[0040] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0041] Please refer to Figure 1 This invention provides a method for batch scheduling of vehicles in a logistics park considering multiple pickup locations, comprising the following steps:

[0042] Based on the actual working conditions of a logistics park, a multi-pickup location vehicle batch scheduling model is constructed, which includes variable descriptions of vehicles and pickup areas, matching constraints between vehicles and pickup locations, operational constraints of vehicles in multiple pickup locations, vehicle batching constraints, etc. Through mathematical modeling, the batch scheduling of vehicles is fully described.

[0043] Based on the characteristic of multi-location pickup operations, minimizing the sum of the operation times of vehicles after batching can be transformed into minimizing the ratio of idle time for pickup locations in each batch. The idle time for pickup locations in each batch is defined as the total idle time of each batch divided by the total operation time. This heuristic information guides vehicle batching.

[0044] In this embodiment, the vehicle operation schedule for a certain day of a steel logistics park is obtained, as shown in Table 1. There are a total of 10 vehicles, numbered I = {1, 2, ..., 10}, and four pickup locations for the operations, numbered J = {J...}. A J B J C J D The operation time of each vehicle at different pickup locations is shown in the figure. ' / ' indicates that the vehicle has no operation plan at that pickup location. The operation time of each vehicle is 40-55 minutes. This method has included the time for moving the vehicle into and out of the pickup location in the operation time.

[0045] Table 1

[0046] I J A ]]> J B ]]> J C ]]> J D ]]> 1 24 / / 24 2 19 / 12 11 3 28 20 / / 4 / 27 / 25 5 20 22 / / 6 / / 27 25 7 / 30 22 / 8 21 / 33 / 9 / / 20 31 10 11 20 / 22

[0047] Since the purpose of vehicle batching is to reduce the number of vehicles arriving at the logistics park at the same time, the heuristic information guiding the batching quantity is either the maximum number of vehicles in each batch or the maximum operating time of each batch. Due to the complexity of vehicle operations at different pickup locations, using the maximum number of vehicles in each batch as the heuristic information for vehicle batching quantity cannot accurately distinguish the workload between different pickup locations. Therefore, we select the maximum operating time of each batch as the heuristic information for vehicle batching quantity. In this embodiment, the maximum operating time of each batch is selected as 80 minutes.

[0048] Based on the above numerical tests, the effectiveness of the proposed vehicle batch scheduling method for logistics parks considering multiple pickup locations was demonstrated. Furthermore, a constrained agglomerative hierarchical clustering algorithm was selected as the heuristic algorithm for solving the vehicle batch scheduling optimization model. The constrained agglomerative hierarchical clustering algorithm is as follows:

[0049] Step 1: Divide each vehicle into a batch, calculate the idle rate after merging batches, and select the batch with the lowest idle rate as a new batch.

[0050] Step 2: Add the new merged batch to the existing batch, continue to calculate the idle rate after merging batches, and select the merged batch with the smallest idle rate as the new batch.

[0051] Step 3: If the job time of the new batch after merging the two batches exceeds the maximum job time of each batch, then the idle rate of the merged batches is defined as infinite.

[0052] Step 4: Repeat the above merging steps until the idle rate after merging any batch is infinite, then stop the merging process and obtain the final vehicle batching result.

[0053] In this example, the results of solving the mathematical optimization model for vehicle batch scheduling using the aforementioned agglomerative hierarchical clustering algorithm are shown in Table 2. The vehicle number is I, the batch is K, and the pickup location for the operation is J = {J}. A J B J C J D Assume that the tasks are performed sequentially starting from the first batch, with the start time being 8:00 AM and a 3-minute interval between batches. The objective function value is f = 136.

[0054] Table 2

[0055] I K J A ]]> J B ]]> J C ]]> J D ]]> 1 2 9:56-10:19 / / 9:31-9:54 2 1 8:28-8:46 / 8:00-8:11 8:47-8:57 3 1 8:00-8:27 8:28-8:47 / / 4 2 / 9:22-9:48 / 9:55-10:19 5 2 9:22-9:41 9:00-9:21 / / 6 1 / / 8:25-8:51 8:00-8:24 7 2 / 9:50-10:19 9:00-9:21 / 8 2 9:00-9:20 / 9:27-9:59 / 9 2 / / 10:00-10:19 9:00-9:30 10 1 8:47-8:57 8:00-8:19 / 8:25-8:46

[0056] As can be seen from the above vehicle batch scheduling plan, the 10 vehicles were divided into two batches. Furthermore, it can be seen from the vehicle operation plan of each batch that the waste rate of operation time and space resources is low, and the idle rate of the pickup position is low.

[0057] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be included in the scope of the present invention.

Claims

1. A method for batch scheduling of vehicles in a logistics park considering multiple pickup locations, characterized in that, Includes the following steps: Step S1: Obtain the operational characteristics of vehicles with multiple pickup locations in the logistics park, and construct a vehicle operation model with vehicle pickup data and logistics park yard cargo placement data as inputs and vehicle pickup operation scheduling plan as output. Step S2: Based on the vehicle operation model, construct a vehicle batch scheduling optimization model with the objective function of minimizing the operation time after batching; Step S3: Based on the vehicle batch scheduling optimization model, solve for the optimal vehicle batching scheme and the corresponding scheduling plan using a heuristic algorithm; The vehicle batch scheduling optimization model is as follows: The objective function is: The constraints are: l,h∈I,j∈J,k∈K,U jk ∈1,2,...|U jk | i∈I,r,m∈J,k∈K,w ik ∈1,2,...|W ik | Where I is the vehicle set, J is the pickup location set, K is the batch set, NI is the total number of vehicles in operation, and G... i T represents the number of pickup locations for vehicle i. k For the operation time of the kth batch of vehicles, u jk w represents the position of the vehicle in the picking position j of the kth batch in the work sequence. ik Let U be the position of the pickup location of the kth batch in the operation sequence of vehicle i. jk For the yard assembly of the kth batch of pickup location j, |U jk |W represents the number of vehicles operating at pickup location j in the kth batch. ik | represents the number of pickup locations for vehicle i in the kth batch of operations. Let be the start time of the operation for vehicle i at pickup location j in the kth batch. Let T be the end time of the operation of vehicle i at pickup location j in the kth batch. ijk Let M be the operation time of vehicle i at pickup location j in the kth batch, and let M be a number greater than a preset value. ik Z takes the value 1 if vehicle i belongs to the kth batch, and 0 otherwise. ijk If vehicle i belongs to the k-th batch and is operating at pickup location j, the value is 1; otherwise, the value is 0. If vehicle i belongs to the kth batch and is the uth in the operation sequence of pickup location j jk If the position is specified, the value is 1; otherwise, the value is 0. If the pickup location j of the kth batch is the wth position in the operation sequence of vehicle i... ik If the position is specified, the value is 1; otherwise, the value is 0.

2. The method for batch scheduling of vehicles in a logistics park considering multiple pickup locations as described in claim 1, characterized in that, Step S3 specifically involves: (1) Divide a single vehicle into a batch, calculate the idle rate after merging batches, and select the merged batch with the smallest idle rate as a new batch. (2) Add the new merged batch to the original batch, continue to calculate the idle rate after merging batches, and select the merged batch with the smallest idle rate as a new batch. (3) If the operation time of the new batch after merging the two batches exceeds the maximum operation time of each batch, then the idle rate after merging the two batches is defined as infinite. (4) Repeat the above merging steps until the idle rate after merging any batch is infinite, then stop the merging process and obtain the final vehicle batching result.

3. A system for batch scheduling of vehicles in a logistics park considering multiple pickup locations, characterized in that, It includes a processor, a memory, and a computer program stored in the memory. When the processor executes the computer program, it specifically performs the steps in the logistics park vehicle batch scheduling method considering multiple pickup locations as described in any one of claims 1-2.

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