On convergence of the multi-objective particle swarm optimizers
作者： Prithwish Chakraborty , Swagatam Das , Gourab Ghosh Roy , Ajith Abraham , None
DOI: 10.1016/J.INS.2010.11.036
关键词:
摘要: Several variants of the particle swarm optimization (PSO) algorithm have been proposed in recent past to tackle multi-objective (MO) problems based on concept Pareto optimality. Although a plethora significant research articles so far published analysis stability and convergence properties PSO as single-objective optimizer, till date, best our knowledge, no such exists for (MOPSO) algorithms. This paper presents first, simple general Pareto-based MOPSO finds conditions its most important control parameters (the inertia factor acceleration coefficients) that govern behavior optimal front objective function space. Computer simulations over benchmark MO also provided substantiate theoretical derivations.
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