The Sybmiosis Coevolution Multiobjective Algorithm And Applications

The Multi-Objective Evolutionary Algorithm (MOEA) has two advantages compared the conventional algorithms in constructing the Pareto set and robust. Coevolution as a kind of promotion mechanism in biology evolution, has been gradually accepted by the MOEA researchers. The investigation results have proved that Coevolution mechanism can accelerate the algorithm and obtain the abundant population diversity. The Multiobjective Coevolution algorithm (MOCEA) now mainly takes a attention in competing mechanism or collaborate mechanism. However the amalgamation of two mechanisms has theoretical meanings.This paper provides a new MOCEA named Symbiosis Coevolution Multiobjective Algorithm (SCMA),which can integrate the competition and collaboration mechanism Through importing the contribution index, we design the collaboration operator, the competition operator and the recomposing operator. These three operators can archive the goal of Coevolution algorithms. Through testing SCMA performance, we compare NSGA2, MOCEA, SPEA2 with SCMA in six benchmark function under three indicator. The result shows that SCMA have a good performance.At the last, we solve two problems based on oil blending and portofolio selection with SCMA. It can provide more choice for management decision.