ISPEA: improvement for the strength Pareto evolutionary algorithm for multiobjective optimization with immunity
Meng Hong-yun, Liu Sanyang · 2004
Recently, there arose some important multiobjective evolutionary algorithms (MOEAs), among these MOEAs, strength Pareto evolutionary algorithm (SPEA) seems the most effective technique for finding or approximating the Pareto-optimal set for multiobjective optimization problems with several characteristics. Unfortunately, there are always some basic and obvious characteristics or knowledge in pending problem, where the loss due to this negligence is sometimes considerable in dealing with complex problems. Based on these reasons, an improvement on SPEA with immunity is given to restrain degeneracy of the evolution process, where the immune operator is realized by vaccine extraction, vaccination and immune selection in turn. Simulations show the ISPEA is effective and feasible.