Vehicle path planning method with time window based on multi-population evolutionary algorithm
A vehicle routing and evolutionary algorithm technology, applied in the direction of calculation, calculation model, instrument, etc., can solve the problems of controlling the total distance cost, the number of vehicles used and the total distance cannot achieve a balance and can not be achieved, so as to reduce the driving distance. Distance cost, reduction in the number of vehicles used, and the effect of increasing diversity
Pending Publication Date: 2022-04-12
ANHUI UNIVERSITY
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[0003] In recent years, with the rapid development of Internet technology, the market of logistics management and other industries has also expanded rapidly, and the number of users has increased sharply. Path planning methods emerge in endlessly, but most of the existing technologies can reduce the number of vehicles used in a service area, and cannot control the total cost of driving distance, or can control the cost of total driving distance, but use more There are too many vehicles, and a balance cannot be reached between the number of vehicles used and the total distance traveled
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[0070] In this implementation example, a vehicle path planning method with a time window based on a multi-population evolutionary algorithm can better explore the feasible region through the weak cooperation of two populations, and through the different emphases of different populations and mutual promotion. The boundary solution improves the efficiency of searching for the least-used vehicles and the shortest total path under the condition of satisfying the time window constraints. Specifically, the vehicle route planning method with time window is applied to a warehouse c 0 , N customers and K transport vehicles in the delivery service area, in the delivery service area, record N customers as c={c 1 , c 2 ,...,c i ,...,c N}, 1≤i≤N; c i represents the i-th customer, let the i-th customer c i The time window of is denoted as [e i , l i ], where e i and l i Respectively represent the i-th customer c i The earliest start time and latest end time of the service; let the...
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The invention discloses a vehicle path planning method with a time window based on a multi-population evolutionary algorithm. The method comprises the following steps: 1, generating an auxiliary problem for a vehicle path problem with a time window; 2, two populations are generated through random initialization, the population 1 is used for optimizing an original problem, and the population 2 is used for optimizing an auxiliary problem; and 3, iteratively optimizing the two populations based on a coevolution algorithm framework, regularly executing local search operation on the two populations until a stop condition is met, and outputting an individual with the highest non-dominated grade in the optimal population as an optimal scheme for vehicle path planning and time arrangement. According to the method, the problem of vehicle path planning with the time window can be solved, and a shorter total driving distance can be obtained while the minimum number of used vehicles is found, so that the transportation efficiency is improved, and the transportation cost is reduced.
Description
technical field [0001] The invention relates to the field of vehicle route planning in the logistics industry, in particular to a vehicle route planning method with a time window based on a multi-population evolutionary algorithm. Background technique [0002] The vehicle routing problem refers to the need for a group of vehicles to find a group of cost-effective routes to meet the needs of different customers. It is a well-known NP-hard combinatorial problem in logistics management, vehicle scheduling, and transportation. If the customer's time window requirements are considered at the same time, then the vehicle routing problem is transformed into a vehicle routing problem with time windows. [0003] In recent years, with the rapid development of Internet technology, the market of logistics management and other industries has also expanded rapidly, and the number of users has increased sharply. Path planning methods emerge in endlessly, but most of the existing technolog...
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IPC IPC(8): G06Q10/04G06Q10/06G06Q10/08G06N3/00
CPCY02T10/40
Inventor 田野孙脉海项小书张兴义
Owner ANHUI UNIVERSITY