A Class Of Intelligent Algorithm In Logistics And Transport - Inventory Joint Optimization Problem In Applied Research

The logistics system is an organic entity, which is composed of transportation, inventory and distribution. The rapid growth of logistics system indicates the strength and the modernization of the country. As the most important process in the logistics system, the execution of transportation and inventory not only plays an important role on the customer's service, but also has an overall impact on the cost control. Owing to the large scale of logistics system, the existing maths methods are not ideal in solving them. As a result, the research on the optimal control solution of the integrated problem on inventory control and transportation shows great significance theoretically and practically.Based on the logistics technology, with the theory of ant colony algorithms and genetic algorithms, the thesis makes a deep research on theories, models and methods aiming at transportation vehicle routing planning, inventory control and the integrated optimal solution of these two problems.In the process of transportation optimization, the thesis firstly designs a basic ant algorithm to solve the VRP problem. Owning to the algorithm's limitation in solving larger scale problem, the thesis makes improvements on the algorithm, and on programs' procedures with MATLAB language to verify the algorithm's excellent performance in accelerating the convergent speed and enhancing the searching ability.In the process of inventory control optimization, based on the EOQ model, the thesis designs the algorithm to solve the inventory supplement problem and to implement the individul's optimization. And then the thesis designs an optimization algorithm to adjust the distribution period. The result of the example shows the algorithm's efficiency on satisfying custom's demand and the distribution center's transportation capacity.In order to solve the integrated problem, the thesis introduces a two-phase method. In the first phase, the thesis divides a whole distribution region into many customer subsets by radius-circle partitioning method, and solves the inventory supplement problem. In the second phase, the thesis introduces improved VRP algorithm to optimize transportation route. Moreover, the thesis testifies the conclusions of theoretical discussion by a logistics case, and illustrates the efficiency of solutions in the integrated optimization problem.