Application Of Genetic Algorithms In Logistics Warehousing Optimization

Since the new century, due to the economic globalization and the supply chain integration, the modern logistics industry is flourishing and playing an increasingly important role in national economic construction. The new means of circulation industry, represented by the chain of distribution business, logistics distribution, e-commerce and so on, develops rapidly and brings a new power for the economic development. As an important part of modern logistics, logistics warehousing plays a vital role in the whole system. Reasonable and efficient warehousing can speed up the flow of goods, lower the costs, ensure the smooth progress of the production and achieve effective control and management of resources.In this paper, inventory control of logistics warehousing has been studied. First the effect of inventory control, including research status of domestic and foreign and the flaws in existing studies is been introduced. And then the theory of inventory control in warehouse management, optimization requirements and main problems of inventory control in modern logistics supply chain are also introduced. On this basis, genetic algorithms is been chosen to solve the problem .The basic idea and use of the process of genetic algorithms are been detailed.This paper establishes a multi-echelon supply chain mode of manufacturers of a variety of products, aims at costs, profits, retailers order response time and customer satisfaction, analyzes the production, transportation, ordering, inventory, cost, and gets the various nodes of input, output and inventories. Then using genetic algorithms the multi-target mixed programming model is been optimized .Finally through an example the feasibility and effective of the model and algorithms is verified.