Research On Electric Power Supply Chain Synergy Based On Intelligent Algorithms And Multi-Agent

In recent years, electric power industry in China has undergone a deep reform. However, there are still some problems, such as production inefficiency, loss of business, low quality of service, and so on. In addition, there are a lot of instability and disharmony problems on production, transportation, sales and other business management process. In this paper, I propose that electric power industry supply chain management is a solution to solve the above problems. This supply chain management covers components including the nodes of supply, production, transportation, inventory and sales. It coordinates and manages the collaborative work of the enterprise; shares information to each other. Ultimately, every enterprise in the supply chain achieves win-win goal.Supply chain synergy problem is a NP-hard linear programming problem and worth researching within electric power industry. In this paper, I will apply the multidisciplinary method, which includes operations research, optimality principle, intelligent algorithm, multi-agent technology, etc. I research the electric power supply chain synergy model, intelligent evolutionary multi-objective optimization algorithm, and negotiation and communication mechanism of Multi-Agent. Finally, I propose a solution of electric power supply chain synergy. I will discuss the procedure as follows:Firstly, most of the researchers focus only on the minimal cost, the maximal customer satisfaction, etc., and ignore the influence of capital flow. Therefore, I propose a multi-objective supply chain model based on Cash Conversion Cycle. Meanwhile, I propose a multi-echelon electric power supply chain model with deterministic demand and a two-echelon electric power supply chain model with stochastic demands, respectively.Secondly, the traditional genetic algorithm and simulated annealing algorithm are easy to premature. I propose the methods of genetic algorithm with improved encoding and improved hybrid simulated annealing genetic algorithm, and apply this method to solve the optimization of above model. The experimental results show that the proposed algorithms can achieve better optimal solutions in shorter time.Thirdly, focus on the lack of traditional negotiation and communication mechanism of Multi-Agent, I propose an improved negotiation and communication mechanism, and apply to the electric power supply chain.Finally, according to the above procedure, this paper proposes a collaborative scheme of electric power supply chain network based on Multi-Agent. It designs an electric power supply chain network prototype system based on Multi-Agent. The prototype system can help the electric power industry to build a supply chain network with optimal characteristics.