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A Short Tutorial on EvolutionaryMultiobjective OptimizationCarlos A. Coello CoelloCINVESTAV-IPNDepto. de Ingenier´ıa El´ectricaSecci´ on de Computaci´ onAv. Instituto Polit´ecnico Nacional No. 2508Col. San Pedro ZacatencoM´exico, D. F. 07300, MEXICOccoello@cs.cinvestav.mxCarlos A. Coello Coello, March 2001. Tutorial on Evolutionary Multiobjective OptimizationWhy Multiobjective Optimization?Most optimization problems naturally have several objectives to beachieved (normally conflicting with each other), but in order tosimplify their solution, they are treated as if they had only one (theremaining objectives are normally handled as constraints).EMO’01Carlos A. Coello Coello, March 2001. Tutorial on Evolutionary Multiobjective OptimizationBasic ConceptsThe Multiobjective Optimization Problem (MOP) (alsocalled multicriteria optimization, multiperformance or vectoroptimization problem) can be defined (in words) as the problem offinding (Osyczka, 1985):a vector of decision variables which satisfies constraints andoptimizes a vector function whose elements represent theobjective functions. These functions form a mathematicaldescription of performance criteria which are usually inconflict with each other. Hence, the term “optimize” meansfinding such a solution which would give the values of allthe objective functions acceptable to the decision maker.EMO’01Carlos A. Coello Coello, March 2001. Tutorial on Evolutionary Multiobjective OptimizationBasic ...
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