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Solving Method of the Optimization Problem of Logistic Distribution Vehicle Scheduling Based on Hybrid Genetic Algorithm

Zhou Feng

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Abstract

The optimization problem of logistic distribution vehicle scheduling is a NP-hard problem.As the scale of the problem increases,it's difficult to get an optimal solution just based on precise algorithms.At first,in-depth analysis of the VSP is made and an optimized mathematic model is built.Then,VSP has been properly divided into two parts properly according to the model,which organically combines the genetic algorithm's entire searching ability with local searching ability of the C-W saving heuristic algorithm.Thus,a hybrid genetic algorithm is constructed.In the end,validation of the above solving algorithm is verified through an application instance.

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What this paper is about

The optimization problem of logistic distribution vehicle scheduling is a NP-hard problem.As the scale of the problem increases,it's difficult to get an optimal solution just based on precise algorithms.At first,in-depth analysis of the VSP is made and an optimized mathematic model is built.Then,VSP has been properly divided into two parts properly according to the model,which organically combines the genetic algorithm's entire searching ability with local searching ability of the C-W saving heuristic algorithm.Thus,a hybrid genetic algorithm is constructed.In the end,validation of the above solving algorithm is verified through an application instance.

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Available abstract

The optimization problem of logistic distribution vehicle scheduling is a NP-hard problem.As the scale of the problem increases,it's difficult to get an optimal solution just based on precise algorithms.At first,in-depth analysis of the VSP is made and an optimized mathematic model is built.Then,VSP has been properly divided into two parts properly according to the model,which organically combines the genetic algorithm's entire searching ability with local searching ability of the C-W saving heuristic algorithm.Thus,a hybrid genetic algorithm is constructed.In the end,validation of the above solving algorithm is verified through an application instance.

Key concepts: Genetic algorithm, Mathematical optimization, Scheduling (production processes), Algorithm, Computer science, Heuristic, Mathematics

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