Wali Khan Mashwani
ABSTRACT
Integration of single methods into their hybrids are researched scarcely in the recent few years. This paper presents the feasibility study for integration of two methods: MOEA/D [7] and NSGA-II [4] in the proposed multimethod search approach (MMTD). During implementation of MMTD, we borrows some concepts from the specialized literature of EMO. In MMTD, the synergetic combination of MOEA/D and NSGA-II can unleash their full power and strength self-adaptively for tackling two set of problems: 1) ZDT test problems [6], 2) cec09 unconstrained test instances [1]. The final best approximated results illustrates the usefulness of MMTD in multiobjective optimization (MO).
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Digital Library
- J. A. Vrugt et. al. Improved Evolutionary Optimization from Genetically Adaptive Mutimethod Search. In Proceedings of PNAS'07,(USA) (Jan, 16 2007), vol. 104, pp. 708--701.Google Scholar
- J. A.Vrugt et al. AMALGAM. IEEE Trans On EC 13, 2 (April 2009), 243--259. Google ScholarDigital Library
- K. Deb et al. NSGA-II. IEEE Trans On EC 6, 2 (2002), 182--197. Google ScholarDigital Library
- Khan, W., and Zhang, Q. MOEA/D-DRA with Two Crossover Operators. In UKCI (8th-10th September 2010), pp. 1--6.Google Scholar
- Q.Zhang et al. Mop Test Instances for the CEC 2009 Special Session and Competition. Technical report CES-487, 2009.Google Scholar
- Zhang, Q., and Li, H. MOEA/D. IEEE Trans On EC 11, 6 (December 2007), 712--731. Google ScholarDigital Library
Index Terms
- Integration of NSGA-II and MOEA/D in multimethod search approach: algorithms
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