The Research Of Three-dimensional Vehicle Filling Problem And Vehicle Routing Problem

Distribution activities are based on customer requirements, for goods picking, processing, combining and so on, and delivered to the designated place. The process of loading and distribution of goods is one of the main activities of distribution activities, one of the main costs of the cost of distribution activities. It can effectively reduce the distribution costs, save logistics cost, improve the profit margins of the enterprise by improving the efficiency of loading of the vehicle and vehicle distribution route optimization.At present the goods loading study more to consider the volume and the weight, in the actual goods loading ignoring the influence of different sizes and specifications of the goods loading, easy to cause the volume and weight meet the vehicle rated capacity, but by the specification size limits the goods can’t be completely loading; Study on the distribution route and vehicle loading mainly in separate research, combine the research from the overall consideration is less. This paper studies the optimization model of goods loading and vehicle routing problem research combining 3D goods loading and vehicle routing combination, in vehicle volume utilization rate, capacity utilization rate and the cost of distribution optimization the goal, cargo stowage and vehicle routing optimization.This paper established the combinatorial optimization model combining the three-dimensional, multi-vehicle loading and vehicle distribution route, considering the size of the goods, size of vehicle, multi-vehicle, the gravity center of the vehicle other constraints. The model takes lowest cost, vehicle volume utilization rate highest, vehicle load utilization rate highest as the optimization objective. In order to solve the three dimensional and multi vehicle loading design the strategy of the remaining space combining, the loading optimization algorithm and loading test algorithm to implement goods loading; choose genetic algorithm as the optimization algorithm, design of chromosome encoding, population initialization algorithm, to determine the selection, crossover, mutation operation rules, to improve the algorithm’s adaptability, reduce the possibility of precocious and accelerate the convergence speed of the algorithm, combined with loading correlation algorithm and genetic algorithm, the realization of the solution of the model.In order to verify the solving effectiveness of the algorithm, using benchmark problems proposed by Gendreau et al to discuss the parameter setting and verifies the solving effectiveness of the algorithm. Comparing with the results of this algorithm and the results of the benchmark problems verified the effectiveness of this algorithm. Finally, with the practical business data of a certain well-known logistics enterprise as the case, collect the customer demand information, location information and other data collection from the enterprise, are solved by the algorithm, and the results were compared with the original scheme, verifies the model algorithm in practical application problems has better effect on solving.