Optimization Of Supply Chain Logistic Facility Location Based On Hybrid Genetic Algorithm

Logistic network plays a role part in enterprise supply chain, which is the foundation of supply chain operation and management, is the primary task of enterprise strategic design. In logistic network logistic facility is a bridge, by which supplier connect with demander, is a signify node. Logistic facility location has great effect on supply chain and enterprise competition. Under the guidance of theories in systematic science and ecological theory, through integrating multi-sciences, issues of supply chain facility location were studied, based stochastic demand.In this paper, we construct an multi-echelon optimization model, which is a stochastic programming, based stochastic demand, synthetically considering inventory, transport and construction optimize problem. This model, which is seasoned with real world, has extraordinary adjustability and flexibility. To solve the problem, we transform stochastic programming into nonlinear programming by model, and we use hybrid genetic algorithm, which combine simulated annealing algorithm accomplished in local searching, with genetic algorithm good at whole researching. In programming this algorithm, we present an efficient gene representation, which save the memory, and improve the speed of solution. An example is given to confirm the availability of the optimization model.