CN112801310A - Vehicle path optimization method based on C-W saving algorithm - Google Patents

Abstract

The invention discloses a vehicle path optimization method based on a C-W saving algorithm. The method mainly comprises the following operation processes: firstly, each customer is individually connected with a recovery network point to form n lines only containing one customer, then the lines are sorted from large to small according to the saved mileage value, and under the maximum load capacity limit value of the vehicle, two corresponding customer points are sequentially inserted into the path until all the customers are inserted into the path, so that the goal of the minimum driving distance of the vehicle is achieved. The vehicle path optimization method based on the C-W saving algorithm formed in the steps belongs to the protection scope of the invention. The invention optimizes the vehicle driving path by utilizing the C-W saving algorithm, improves the transportation efficiency and reduces the transportation cost of enterprises.

Description

Vehicle path optimization method based on C-W saving algorithm

Technical Field

Aiming at the problem of optimizing the vehicle path from one recovery network point to a plurality of customers in the recovery process of waste electric and electronic products, the C-W saving algorithm is applied to the aspect of vehicle scheduling optimization, so that the driving path from the recovery network point to the customers is optimized, and the vehicle transportation distance is minimized. The saving algorithm is a heuristic algorithm for solving the problem of uncertain number of transport vehicles and is commonly used in the field of logistics. And aiming at the characteristics of products transported in the logistics of the assembly enterprise, constraint conditions are inserted in the line planning so as to meet the special logistics requirements. Therefore, it belongs not only to the logistics field but also to the intelligent information field.

Background

The prosperity of social economy and internet industries cannot keep away from the high-speed development of the logistics distribution industry. Logistics distribution is an extended service which is developed by enterprises facing intense competition, and the high cost of logistics is a major problem facing the enterprises. The reasonable planning of the distribution path has a significant influence on the logistics distribution cost, so an efficient distribution scheme must be formulated to reasonably complete the cargo distribution of all demand points in the logistics network. In vehicle path planning, the goals of minimum vehicle usage, shortest driving distance, minimum intermediate links and minimum transportation cost are achieved, and meanwhile, the response time and the satisfaction degree of customers are ensured, so that the efficient and reasonable path distribution is necessary for reducing the enterprise cost.

The vehicle path optimization method based on the C-W saving algorithm is designed, the total transportation distance from a recovery network point to a customer can be minimized, the vehicle running path is displayed, optimal vehicle running is achieved, and the enterprise logistics cost is reduced.

Disclosure of Invention

A vehicle path optimization method based on a C-W saving algorithm mainly comprises the following operation processes: the 'saved mileage' between any two customers is firstly solved, and then the routes are sorted in the order from big to small and reasonably and efficiently distributed. The method utilizes a C-W saving algorithm to enable the total travel of all vehicles to be shortest. The method is characterized by comprising the following steps:

1. a vehicle path optimization method based on a C-W saving algorithm is characterized in that a vehicle scheduling model is established aiming at the vehicle path planning problem from a sorting center to a plurality of clients, and an optimal driving route is determined by utilizing the C-W saving algorithm;

the method is characterized by comprising the following steps:

step 1: modeling based on problems

Suppose that a recovery site has K transport vehicles, K ═ 1, 2.. m } is a vehicle set, and suppose thatSetting all vehicles to be of one type, wherein the maximum load capacity is q; the recycling network site recycles waste electric and electronic products to n customers, wherein V & ltd & gt is {0,1,2,.. n } represents a customer set, and A & ltd & gt is { d_ijI, j belongs to V, i is not equal to j represents the linear distance between two clients; the ith stock of the customer goods is g_iAnd g is_iQ ≦ q, ensuring that a customer is delivered by only one vehicle. The goal of the vehicle path optimization problem is to properly arrange the transport vehicles and determine the transport route for each vehicle to ensure that the transport distance is the shortest. In addition, we present the following constraints:

1) each customer is delivered by only one vehicle:

wherein, y_ikIndicating that the kth vehicle is responsible for the transportation of the ith customer, i indicates the ith customer, and i belongs to V; k denotes the kth vehicle, K ∈ K.

2) Vehicle k travels from customer i to customer j:

wherein x is_ijkIndicating that vehicle k is traveling from customer i to customer j.

3) The total delivery volume of each line does not exceed the maximum load capacity of the vehicle:

wherein, g_iIndicating the inventory of the ith customer's items,

representing the total delivery per line.

The objective function of the vehicle path optimization problem is:

wherein d is_ijRepresenting the distance from client i to client j.

Step 2: and calculating the shortest distance from the recovery network point to the customer and between different customers on the premise that the geographic position of each city is known. The solution to the vehicle path optimization problem is a set of paths that traverse all of the customers. Let the coordinates of two clients be (x)_i,y_i)、(x_j,y_j) Wherein x is_iAbscissa, y, representing the location of client i_iIndicating the ordinate. Calculate its distance c_ij：

And step 3: calculating the saved mileage, comprising the following steps:

step 3.1-calculating the saved mileage P_ij:

p_ij＝c_i,0+c_0,j-c_ij (6)

Wherein, P_ijRepresents the saved mileage of client i and client j, c_ijRepresents the distance from client i to client j, c_i,0Representing the straight-line distance between customer i and the recycling site, c_0,jRepresenting the straight-line distance between customer j and the recycling site.

And 3.2, sorting the saved mileage in a descending order and storing the sorted saved mileage number in a set S, wherein S is { P ═ P_ij|P_ij> 0 }. And if the S is the empty set, finishing the calculation. Otherwise, for P in S_ijCustomer points of interest s_i、s_jJudging whether the following conditions are met:

(1)s_i、s_jare not on the constructed path;

(2)s_iand s_jOne is a path starting point and one is a path end point;

(3)s_iout of path, s_jIs the starting point of the path;

(4)s_iout of path, s_jIs the end point of the path.

If one of the above conditions is satisfied, go to step 4, otherwise delete the current P from S_ij。

And 4, step 4: connection s_iAnd s_jFor a path, judging that s is contained_iAnd s_jIf the total amount of all the customer's goods on the route of (1) meets the requirement of the maximum load capacity of the vehicle, if so, it is recorded as v_l(l 1,2, …, n) and add to the Route set Route, determine the next group P_ijTo the customer site s_i、s_jWhether a connection can be made as a path.

And 5: and repeating the contents in the steps 3 and 4 until the S is an empty set.

The invention is mainly characterized in that:

the invention relates to a vehicle path optimization method based on a C-W saving algorithm, which aims at the problem of vehicle path optimization from a waste electrical and electronic product sorting center to a plurality of clients. The method has the advantages of simplicity, high efficiency and convenience in execution.

Drawings

FIG. 1 is a schematic illustration of mileage savings in the present invention;

FIG. 2 is a vehicle routing diagram of the present invention for a recovery network to various customers.

Detailed Description

A vehicle path optimization method based on a C-W saving algorithm mainly comprises the following operation processes: the 'saved mileage' between any two customers is firstly solved, and then the routes are sorted in the order from big to small and reasonably and efficiently distributed. The method can realize the aim of the shortest total driving mileage of the vehicle. The method is characterized by comprising the following steps:

1. a vehicle path optimization method based on a C-W saving algorithm is characterized in that a vehicle scheduling model is established aiming at the vehicle path planning problem from a sorting center to a plurality of clients, and an optimal driving route is determined by utilizing the C-W saving algorithm;

the method is characterized by comprising the following steps:

step 1: modeling based on problems

The recovery network point is assumed to have K transport vehicles, wherein K is a vehicle set, all vehicles are assumed to be of one type, and the maximum load capacity is q; the recycling network site recycles waste electric and electronic products to n customers, wherein V & ltd & gt is {0,1,2,.. n } represents a customer set, and A & ltd & gt is { d_ijI, j belongs to V, i is not equal to j represents the linear distance between two clients; the ith stock of the customer goods is g_iAnd g is_iQ ≦ q, ensuring that a customer is delivered by only one vehicle. The goal of the vehicle path optimization problem is to properly arrange the transport vehicles and determine the transport route for each vehicle to ensure that the transport distance is the shortest. In addition, we present the following constraints:

4) each customer is delivered by only one vehicle:

wherein, y_ikIndicating that the kth vehicle is responsible for the transportation of the ith customer, i indicates the ith customer, and i belongs to V; k denotes the kth vehicle, K ∈ K.

5) Vehicle k travels from customer i to customer j:

wherein x is_ijkIndicating that vehicle k is traveling from customer i to customer j.

6) The total delivery volume of each line does not exceed the maximum load capacity of the vehicle:

wherein, g_iIndicating the inventory of the ith customer's items,

representing the total delivery per line.

The objective function of the vehicle path optimization problem is:

wherein d is_ijRepresenting the distance from client i to client j.

Step 2: and calculating the shortest distance from the recovery network point to the customer and between different customers on the premise that the geographic position of each city is known. The solution to the vehicle path optimization problem is a set of paths that traverse all of the customers. Let the coordinates of two clients be (x)_i,y_i)、(x_j,y_j) Wherein x is_iAbscissa, y, representing the location of client i_iIndicating the ordinate. Calculate its distance c_ij：

And step 3: calculating the saved mileage, comprising the following steps:

step 3.1-calculating the saved mileage P_ij:

p_ij＝c_i,0+c_0,j-c_ij (6)

Wherein, P_ijRepresents the saved mileage of client i and client j, c_ijRepresents the distance from client i to client j, c_i,0Representing the straight-line distance between customer i and the recycling site, c_0,jRepresenting the straight-line distance between customer j and the recycling site.

And 3.2, sorting the saved mileage in a descending order and storing the sorted saved mileage number in a set S, wherein S is { P ═ P_ij|P_ij> 0 }. And if the S is the empty set, finishing the calculation. Otherwise, for P in S_ijCustomer points of interest s_i、s_jJudging whether the following conditions are met:

(5)s_i、s_jare not on the constructed path;

(6)s_iand s_jOne is a path starting point and one is a path end point;

(7)s_iout of path, s_jIs the starting point of the path;

(8)s_iout of path, s_jIs the end point of the path.

If one of the above conditions is satisfied, go to step 4, otherwise delete the current P from S_ij。

And 4, step 4: connection s_iAnd s_jFor a path, judging that s is contained_iAnd s_jIf the total amount of all the customer's goods on the route of (1) meets the requirement of the maximum load capacity of the vehicle, if so, it is recorded as v_l(l 1,2, …, n) and add to the Route set Route, determine the next group P_ijTo the customer site s_i、s_jWhether a connection can be made as a path.

And 5: and repeating the contents in the steps 3 and 4 until the S is an empty set.

Data samples

Tables 1-12 are data from the experiments of the present invention. Table 1 is a transportation odometer of the present invention, showing the linear distance from each customer to the recycling site and between each customer; table 2 is the savings odometer for any two customers in the present invention; table 3 is a saving odometer arranged from large to small.

TABLE 1 transport odometer

0	0	0	0	0	0	0	0	0	0	0
											46.0109	0	0	0	0	0	0	0	0	0	0
42.0119	81.7068	0	0	0	0	0	0	0	0	0
											20.0250	33.1059	62	0	0	0	0	0	0	0	0
8.5440	42.8019	50.1597	12.6491	0	0	0	0	0	0	0
											53.1507	99.1564	36.0555	69.9714	57.6888	0	0	0	0	0	0
29.4109	59.6657	24.0832	46.8188	37.7539	54.4059	0	0	0	0	0
											20.1246	43.0813	60.8276	10.1980	11.6619	63.5610	49.3964	0	0	0	0
31.9061	15.6525	70.8308	17.4642	27.5862	84.8116	51	27.5136	0	0	0
											33.2415	76.2758	46.6690	43.9318	33.1448	31.1448	51.2445	35.4683	60.8030	0	0
21.9317	56.7979	55.1543	23.7065	17.0294	51.2445	49.5782	14.2127	41.1461	21.6333	0

TABLE 2 Mileage saving

TABLE 3. order the saved mileage from big to small

Claims (1)

1. A vehicle path optimization method based on a C-W saving algorithm is characterized by comprising the following steps:

step 1: modeling based on problems

The recovery network point is assumed to have K transport vehicles, wherein K is a vehicle set, all vehicles are assumed to be of one type, and the maximum load capacity is q; the recycling network site recycles waste electric and electronic products to n customers, wherein V & ltd & gt is {0,1,2,.. n } represents a customer set, and A & ltd & gt is { d_ijI, j belongs to V, i is not equal to j represents the linear distance between two clients; the ith stock of the customer goods is g_iAnd g is_iQ is less than or equal to q, so that a client is guaranteed to be distributed by only one vehicle; the goal of the vehicle path optimization problem is to rationally arrange the transport vehicles and determine the transport route for each vehicle, thereby ensuring the shortest transport route; in addition, the following constraints are given:

1) each customer is delivered by only one vehicle:

wherein, y_ikIndicating that the kth vehicle is responsible for the transportation of the ith customer, i indicates the ith customer, and i belongs to V; k represents the kth vehicle, and K belongs to K;

2) vehicle k travels from customer i to customer j:

wherein x is_ijkIndicating that vehicle k is traveling from customer i to customer j;

3) the total delivery volume of each line does not exceed the maximum load capacity of the vehicle:

wherein, g_iIndicating the inventory of the ith customer's items,

representing the total delivery volume of each line;

the objective function of the vehicle path optimization problem is:

wherein d is_ijRepresents the distance from customer i to customer j;

step 2: on the premise that the geographic position of each city is known, calculating the shortest distance from the recovery network point to the customer and the shortest distance between different customers; the solution to the vehicle path optimization problem is a set of paths that traverse all customers; let the coordinates of two clients be (x)_i,y_i)、(x_j,y_j) Wherein x is_iAbscissa, y, representing the location of client i_iRepresents the ordinate; calculate its distance c_ij：

And step 3: calculating the saved mileage, comprising the following steps:

step 3.1-calculating the saved mileage P_ij:

p_ij＝c_i,0+c_0,j-c_ij (6)

Wherein, P_ijRepresents the saved mileage of client i and client j, c_ijRepresents the distance from client i to client j, c_i,0Indicating customer i to returnStraight-line distance between collection points, c_0,jRepresenting the straight-line distance between the customer j and the recycling website;

and 3.2, sorting the saved mileage in a descending order and storing the sorted saved mileage number in a set S, wherein S is { P ═ P_ij|P_ij> 0 }; if the S is an empty set, the calculation is finished; otherwise, for P in S_ijCustomer points of interest s_i、s_jJudging whether the following conditions are met:

(1)s_i、s_jare not on the constructed path;

(2)s_iand s_jOne is a path starting point and one is a path end point;

(3)s_iout of path, s_jIs the starting point of the path;

(4)s_iout of path, s_jIs a path end point;

if one of the above conditions is satisfied, go to step 4, otherwise delete the current P from S_ij；

And 4, step 4: connection s_iAnd s_jFor a path, judging that s is contained_iAnd s_jIf the total amount of all the customer's goods on the route of (1) meets the requirement of the maximum load capacity of the vehicle, if so, it is recorded as v_l，_l1,2, …, n, and adds the path set Route to judge the next group P_ijTo the customer site s_i、s_jWhether a connection can be made as a path;

and 5: and repeating the contents in the steps 3 and 4 until the S is an empty set.

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