Research On Optimizing Model And Algorithm For Logistics Distribution System Under Electronic Business

With the development of internet and information technique, e-business affects economic life more and more. It becomes the important problem facing with e-business logistics industry that how to make decisions on logical facility location, demand assignment, transportation mode and routing selection, establish high efficient distribution system so as to reduce the distribution cost and improve service quality.First of all, the study research on location model and appraisal method of the logistics distribution center under e-business. According to the different distribution network and strategy, establish the scattered distribution center location model based on time-cost and hybrid distribution center location model based on service-cost. For the restrain condition of scattered distribution center and the characteristics of multi-variable with 0-1, solve the problem adopting the heuristic algorithm based on decomposition-filtration. Considering the characteristics of more node of hybrid location model and uncertainty of standby location center, solve the problem adopting three-stage heuristic algorithm based on fuzzy C-means clustering algorithm and scanning method. Because distribution center location is complex system engineering, it needs to make decisions with qualitative method. Therefore, establish fuzzy appraisal model with multi-criterion and multi-hierarchy. The weight of criterion in model can be gotten based on fuzzy AHP of distribution with proportion. The weight of sub-index can be gotten through calculating fuzzy appraisal value and expected value. The weight of appraisal index of location scheme is the combination of the weight of criterion and the weight of sub-index under the corresponding criterion. The aims of confirming scheme is to make decisions. According to the result of quantitative calculation and qualitative analysis, confirm the optimal scheme using coordinated analysis.Secondly, research on the optimization problem of vehicle scheduling problem under e-business. In order to satisfy with the individual and various demand of customer under e-business, respectively establish vehicle scheduling problem model with multi-restrain condition, vehicle scheduling with picking- delivery model and vehicle scheduling model with time-windows. According to multi-restraint condition and the characteristics of model, design hybrid genetic algorithm based on improved ordered crossover operator and introduced climbing algorithm. Emulation and calculation prove that it is better than improved genetic algorithm and standard genetic algorithm from the side of not only the stability of algorithm but also optimization result through. To picking-delivery model with multi-distribution center, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm. The emulation and calculation proves that it is better than only using genetic algorithm and taboo searching algorithm. For waiting expense and delaying expense affecting distribution cost in vehicle scheduling problem with time windows, the minimum expense is the optimal aim considering distribution route. And design improved two-stage algorithm to solve the problem. The emulation and calculation prove that this algorithm has the characteristics of simple, clear and flexible and it can offer the thought to settle the practical problem in scale.Finally, the study proposes the location routing problem model with time windows of picking-delivery under e-business. Considering that the traditional multi decomposition algorithm is easy to get into partial optimization solution, and not overall optimization solution, the study deign hybrid heuristic algorithm to solve the location routing problem model of picking-delivery as a whole. Firstly, establish weak initial feasible solution based on hybrid clustering algorithm and improved center method. Secondly, create strong initial feasible solution based on improved insertion method. Lastly, optimize the solution with taboo searching algorithm. The emulation and calculation proves that this algorithm has good searching performance and high constringency speed. For location routing problem with time windows, solve the problem using hybrid genetic simulating annealing algorithm as a whole. Adopt the hybrid code based on vector. Introduce the individual amount control selection strategy. To route and location sub-branch, execute the operation of keeping the operation maximum reservation crossover point and single crossover point. Adopt the optimization gene protection strategy as a whole. And control crossover and variation operation using the Boltzmann mechanism of adaptive mutation operator and simulated annealing algorithm. The emulation and calculation prove that this algorithm is better than only using genetic algorithm and simulated annealing algorithm from the side of searching result, solving quality, calculation efficiency and algorithm stability.According to model and algorithm, the study offers the case analysis. The emulation and calculation prove that the model and algorithms is effective.