الفهرس 
Optimization BackgroundOnly 14 pages are availabe for public view
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Abstract
When solvingamulti-objective optimization problem(MOPs),it is of tennot possible to improve one objecti vewi thoutdeterioratingano ther conflictingone.Therefore ,multi-objective optimization is chall enged to determinetheseto fsolutions thatachievethe best compromisewithre spect to allobjectives. Inorder to identify such solutions,the concept of Pare to dominance has been used. It offers away to comparesolutions and to classify the mintonon-dominated and dominated solutions. Asolutiondominatesano theroneifitisatleastas good as the otherinall objectives and itisstrictly better than theotherinatleastone objective.Al thoughagreatdeal ofef for thas been devotedtosolvemulti-objectiveoptimizationproblems,the proble miss till openand there lated issuess tillattracttheinterestof researchers.Mostof the proposedapproa chesmakeuseof meta-heuristics. Pare to based meta-he uristicsforMOP saimtointroduce Pare to dominanceinto nature inspiredalgori thms. Population based meta-heuristicssuchas Gene ticAlgorithms(GAs)< and Particle Swarm Optimization(PSO)are particularlyattracti vetoMO Psasthey providemulti ple non-dominatedsolutionsinasinglerun.