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Logistics is an emerging discipline, distribution is an important content of modern logistics, and transportation cost in logistics cost occupies a high proportion, reasonable arrangement of vehicle distribution route can reduce transportation costs, improve economic efficiency, in the logistics scheduling, vehicle routing problem is a kind of combinatorial optimization problem with a broad range of applications. This article first introduces the genetic algorithm in solving simple constraints application on vehicle routing problem, improved crossover operator, to study the full vehicle optimization scheduling problem of genetic algorithm are fully prepared. Is analyzed in detail in this paper the mathematical model of full vehicle transportation problem, calculated with Floyd algorithm PeiSongDian the shortest distance between the matrix and the corresponding shortest path matrix, using sweep algorithm to allocate tasks, using genetic algorithm (ga) for each set of tasks per car route sort, is equivalent to solving traveling salesman problem, in case the superiority of the proposed algorithm. Multi-objective optimization algorithm is analyzed in this paper, a multi-objective genetic algorithm by constructing the dominating sets, and then to the dominant concentration of individual selection, crossover and mutation operation, and the next generation of population, and, finally, analyzes the deficiency and the future development of this paper.
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