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This paper gives a concise overview of evolutionary algorithms formultiobjective optimization. A substantial number of evolutionary computationmethods for multiobjective problem solving has been proposed so far, and anattempt of unifying existing approaches is here presented. Based on afine-grained decomposition and following the main issues of fitness assignment,diversity preservation and elitism, a conceptual global model is proposed andis validated by regarding a number of state-of-the-art algorithms as simplevariants of the same structure. The presented model is then incorporated into ageneral-purpose software framework dedicated to the design and theimplementation of evolutionary multiobjective optimization techniques:ParadisEO-MOEO. This package has proven its validity and flexibility byenabling the resolution of many real-world and hard multiobjective optimizationproblems.

A Unified Model for Evolutionary Multiobjective Optimization and its Implementation in a General Purpose Software Framework: ParadisEO-MOEO