Research On Multi-Objective Evolutionary Algorithm Based On Artificial Immune System

With the development of society, optimization problem in the present world is gradually affected by a variety of factors, then multi-objective optimization problem arises. Multi-objective optimization problem is a very important subject in research and application of the algorithm, multi-objective optimization aroused extensive attention by scholars. Genetic algorithm is a general optimization in the genetic and evolutionary process and the formation to optimize. Evolutionary algorithm can effectively solve the complex problems, which is due to its advantages and robustness. Multi-objective evolutionary algorithm has been widely used in natural science and engineering and so on many fields.This paper first introduces procession of multi-objective optimization problem, the background and research status, the concept of evolutionary algorithm principle and the typical evolutionary algorithm, then presents a decomposition multi-objective evolution-nary algorithm based on distribution estimation.According to the optimal solution of the problem diversity, uniformity and efficiency of algorithm are studied. The numerical analysis and experiment show that the improved new algorithm not only possesses the advantages of the original algorithm, but also improve the running speed of the algorithm. Applied to the scheduling problem of water supply, under the premise of without any increase in operating costs, improve the efficiency of pumping station and saving some time.The paper contains following tasks:1. This paper briefly introduces the development and research status of the artificial immune algorithm and multi-objective optimization problem.2. Briefly introduces the basic principle of the artificial immune algorithm, and algorithm flow, analysis the advantages and disadvantages of algorithm.3. Briefly introduces the basic concept and the mathematical principle of the multi-objective evolutionary algorithm.4. In order to improve the distributive and uniformity of the algorithm, and reduce the computing time, a new multi-objective artificial immune algorithm based on crowding-density is proposed. The data of experiments shows superiority of the algorithm. 5. The new algorithm is applied to dynamic vehicle routing problem, the experimental results show that the superiority of the improved algorithm.