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Multiobjective evolutionary algorithms: A survey of the state of the art
2011
Swarm and Evolutionary Computation
A multiobjective optimization problem involves several conflicting objectives and has a set of Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary algorithms (MOEAs) are able to approximate the Pareto optimal set in a single run. MOEAs have attracted a lot of research effort during the last 20 years, and they are still one of the hottest research areas in the field of evolutionary computation. This paper surveys the development of MOEAs primarily during
doi:10.1016/j.swevo.2011.03.001
fatcat:jfcghitjp5ap5he4d3ackhhjsu