Research On Energy Distribution Problem Based On Artificial Fish Swarm Algorithm

Material distribution plays a very important role in the process of logistics activity, which is directly associated with consumers. However, the cost of distribution has a high proportion in the total cost of logistics. How to adopt a more scientific and reasonable distribution method has gradually become the focus of the problem. In some aspects of reducing transportation costs and cutting delivery time, people made a lot of exploration and research, and energy distribution problem is a kind of material distribution problem.So all kinds of intelligent optimization algorithms have emerged, such as genetic algorithm, artificial bee colony algorithm, ant colony algorithm, simulated annealing algorithm and artificial fish swarm algorithm, etc. These algorithms provide a new thought, method and tools to solve energy distribution problem. But energy distribution problem is very complex and special, which belong to NP-hard (non-deterministic polynomial). Only by using basic intelligent algorithm, the satisfactory optimal solution doesn’t get. So the basic bionic intelligent algorithm need to be improved and innovated continuous.The paper uses the improved artificial fish swarm algorithm to solve the energy distribution problem of the coal company. The artificial fish algorithm exists limitations, rapid convergence in the early will lead to search the optimal area that is difficult and the instability convergence in the late will lead to the inaccuracy result. For the lack of artificial fish swarm algorithm, the paper makes improvements. First, the concept of virtual artificial fish is introduced to make improvements about the behavior of the basic algorithm of artificial fish swarm, which can expand the range of artificial fish searching and improve the precision of global searching in the early of the algorithm. Then. Combing he attenuation factor introduced with simulated annealing algorithm, the result of local optimization is better. In addition, the simulated annealing algorithm is improved by bringing the second exchange.which can play the advantages of hybrid algorithm and compensate the disadvantage of low accuracy in the late of convergence. The Combination artificial fish swarm algorithm with the genetic algorithm, gives a new mixed algorithm.Finally.the optima performance of mixed algorithms is compared.In order to make better optimization results for complicated energy distribution.the problem is divided into two steps in this paper. The first step is the choice of the loading scheme.the second step is the searching of the distribution road.and the model is constructed respectively. Finally, the problem is coded and makes the simulation experiment and the comparison with basic algorithm.Through the contrast and analysis, the conclusion is draw tha.t the improved artificial fish algorithm and improved hybrid artificial fish algorithm have more advantages to deal with the problem of energy distribution than the basic artifical fish swarm algorithm.