An improved genetic algorithm for solving the vehicle routing problem with time windows
نویسندگان
چکیده
Many practical transport logistics and distribution problems can be formulated as the vehicle routing problem with time windows (VRPTM). The objective is to design an optimal set of routes that services all customers and satisfies the given constraints, especially the time window constraints. The complexity of the VRPTW requires heuristic solution strategies for most real-life instances. However, the VRPTM is a combination optimization problem and is a NP-complete problem, so we can’t get satisfying results when we use exact approaches and normal heuristic ones. In this paper, an improved genetic algorithm to solve the VRPTM problem is developed, which use an improved Route Crossover operator (RC’) and can meet the needs for solving VRPTM problem. Computational experiments show that the GA based on RC’ can obtain a general optimality for all evaluated indexes on the premise of satisfying every customer’s demand and its performance is superior to the GA based on PMX or RC.
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