Research On Green Supply Chain Coordination Evolution Based On Swarm Intelligence

Chinese economy has been developing rapidly, the level of industrialization has been greatly improving, the past our country go is depend on the high consumption of resources, the resource of support the economic development consumption is very serious. At present, high energy consumption, high emission and high pollution in China’s economic operation is still severe, resources shortage restricts economic development, sustainable development is faced with serious challenges.Green supply chain management is combining the environmental protection and supply chain management new management concept, its core idea is the key factor in supply chain management business process of circulation in the comprehensive consideration of environmental protection and manufacturing resources optimization utilization. It not only ensure that the products of green added value realization, but also to promote green consumption, adjust the industrial structure and supply chain resources reasonable use fully played a positive role.So, with focus on the core enterprise in green supply chain are lack of green autonomy, don’t subdivide terminal consumer market and devote green product insufficiently. Government departments on the green enterprises lack of effective supervision policy and the green enterprise incentive mechanism.With the help of evolutionary game theory and particle swarm algorithm for green supply chain collaborative optimization study, this article tried to present based on the swarm intelligence of the green supply chain coordination evolution model. The main work of this paper is as follows:1、According to the terminal consumer market with green economic burden product feedback, constructing the evolutionary game model between the core enterprise and supervision department in green supply chain, it will response the customer demand to product circulation process accurately and effectively, establishing demand function of differentiation management and analysis,which constitute the core enterprises and supervision departments to adopt" green " strategy or not taken " green " strategy with different payoff matrix, then using the replicated dynamic equation to calculate evolutionary stable strategy, the green supply chain benefits maximization strategy. Under the circumstances of evolutionary stable strategy, we draw making groups of dynamic evolution game trajectory map, in order to solve the problem of green supply chain the core enterprise and supervision department coordination optimization problem. According to the green model and the dynamic evolutionary game trajectory map, put forward about the core enterprise and supervision management decision scheme, for the future implementation of green supply chain, constructing the sustainable economic development and industrial upgrade provides the reasonable proposal.2、Paper presented a new particle swarm optimization based on evolutionary game theory (EPSO) for discrete combinatorial optimization to overcome the disadvantages of premature convergence and stagnation phenomenon of traditional particle swarm optimization algorithm (PSO). we give experimental examples in the standard library LIBTSP and the performance analyses of the algorithm. Comparing with the genetic algorithm and basic particle swarm optimization algorithm we show that the EPSO algorithm is effective. And got the conclusion that the different parameters decide the different model in which may have different coordinate act on key parameters.3、Given an example as the textile industry, in the green supply chain industrial cluster evolution stable strategy, the core enterprises using EPSO algorithm to solve unit path on the income loss in industry cluster, in order to the sharing of knowledge and technology. We make the qualitative and quantitative analysis about overall benefits of the textile industry, to improve the objectivity and accuracy of the results.