Self-adaptive evolutionary programming algorithm of multi-objective fuzzy optimal operation

A new global or near global optimization method, called self-adaptive evolutionary programming is proposed in this paper. The new algorithm includes two important aspects. First, a new modal of mutation which primely reflects the principle of organic evolution in nature is presented. Secondly, the mutation operator is self-adaptive during the optimization. Furthermore, the new method and fuzzy set theory is used for solving multiobjective optimal operation problem with soft constraints. Some corresponding technical problems, such as model optimized, genetic operation et al are investigated. Numerical results show that the new algorithm not only has the strong self-adaptability, versatility and the global optimization capability of escaping local optimum, but can reduce the CPU time effectively.