Research Of The Inventory Control And Transportation Decision-making Integrated Optimization Problem Based On Genetic Algorithm

Inventory control and logistics management are the two central part in the decision-making,and plays a very important role in modern logistics. Inventory Control enterprises is one of the major means to reduce operating costs and maintaining the day-to-day business operation of production; transport decision-making is the link between production and marketing. It keep the relation is smooth and raising the level of customer service. In the traditional theoretical research,two issues each have made a lot of research results.However,in the background of accelerate competition in international market,supply chain management has been getting a rapid development and extensive application.Modern logistics take more emphasis on coordination of management system gradually.Theoretical study need a new view of the coordinated operation between inventory control and transportation decision-making on a higher basis to make these two part with the known "back-efficiency" effect realize improvement of overall system performance.This is the starting point of this paper:Put the most important two parts in logistics systems which are inventory control and transportation decision into a big problem,to seek the optimal solution of the joint problem.So far,although the scholars have started to study the joined problem of inventory control and transportation decision-making,it is still a difficult problem to analyze the integrated problem in theory and to use mathematical language to describe the integrated problem for further studying.While how to make it easier to use theoretical research results into practical applications is of great significance and necessary,so to the point of departure for the study,used system analysis method,based on genetic algorithm,this paper discussed the mathematical model and conclusion characteristics of the optimization of inventory control and transport policy integrated issues at random demand conditions.First,this paper summarized the different description of different scholars about the problem,highlighting its focus and classification,and introduced the theoretical and practical significance of the research on inventory control and transportation decision-making integrated optimization problems.Then it gave a category summary about the domestic and foreign research done at status quo and pointed out the shortcomings and some of the potential areas of research,which are conducive to the further deepening and expansion of the study.Secondly,after the carefully analysis of the problem we established the optimization model of inventory control and transport policy integrated problems under the conditions of random demand and(s,Q)inventory requirements.The basic model assumptions:suppliers and retailers component a single multi-network structure and only considering the movement of one goods;Retailers demand is random,and obey Poisson distribution whose parameter isλ;and the supplier's inventory replenishment strategy obey(s,Q)strategy.Then,we used genetic algorithms which is faster on the model to solve the problem.In order to effectively curb groups premature,we have also introduced a specially doped operator which enriched the diversity of individual stocks and the precocious probability greatly reduced. Finally,we used experiment to give a simulation about the problem. Simulation results show that under normal circumstances the cost of integration strategy of distribution and warehousing vendor is less than the cost of separately strategy of warehousing and distribution.In the final analysis,a comparative study of different parameter's impaction to the result of experiments was also given,in witch showed As for single orders,inventory costs h for a unit,Poisson parametersλand the largest number of iteration's impaction to the result of experiments.