Research On Cigarette Vehicle Demand Planning Of Multi-Constraint Conditions

China tobacco industrial enterprise are facing serve competition situation, and China tobacco also made it clearly that "Tobacco Logistic" is the core business. Therefore, the tobacco industry enterprises have to improve its logistics level by using advanced management ideas and logistics technology, so as to obtain the advantage in the competition.Based on the current situation of ZJTI’s logistic, this dissertation select the vehicle demand plan during the peak time with the aim of maximizing the efficiency for research. This dissertation establishes cigarette vehicle demand planning model of multi-constraint conditions by using the 0-1 integer programming model, and genetic algorithm is applied to solve the model of vehicle demand plan. The application of the model is realized through the information system, and the practical results show that the application is effective to improve the efficiency of warehouse.The contents of each chapter are as follows:First chapter:Introduction. This chapter explains the research background, significance and the content, include the background of China Tobacco, the application status of logistics technology in tobacco enterprises, and ZJTI’S cigarette logistics current situation and existing problems.Second chapter:Literature review. The essence of vehicle demand planning problem is a combinatorial optimization problem, this chapter summarize and analyze the literature on the 0-1 programming problem, aircraft landing scheduling and intelligent algorithms.Third chapter:The problem research and data analysis. This chapter describes the characteristics of ZJTI’s tobacco logistics and supply chain system, and analyzes ZJTI’s logistics system of warehouse from information flow and objects flow. This chapter also completed the date acquisition and processing of operation ability.Fourth chapter:Research on model and algorithm of vehicle demand plan. This chapter established vehicle demand planning model. In the model, the maximum contribution to the library as the objective function, and the platform, the forklift, handling group as the resources constraint. Genetic algorithm is applied to solve the model of vehicle demand plan, and this chapter also describes the whole process of genetic algorithm.Fifth chapter:The example calculation and the application of model. This chapter through calculation of practical example to prove the effectiveness of the algorithm, and introduces the actual situation and effect of application.Sixth chapter:Summary and prospect. This chapter summarized the content of this dissertation, and proposed the improvement and development direction of model.