A multimethod search approach based on adaptive generations level
Wali Khan Mashwani · 2011
Integration of single methods into hybrid are researched scarcely in the recent past. This paper investigates the effect of integration of single methods: MOEA/D [1] and NSGA-II [2] in a multimethod search approach, so-called, MMTD, based on self-adaptive generations level proposed in this paper. During implementation, MMTD borrows some concepts from the specialized literature of evolutionary multi-objective optimization (EMO). The synergetic combination of MOEA/D and NSGA-II can unleash their full strength and biases self-adaptively in MMTD framework and can solve efficiently two set of problems: 1) ZDT test problems [3], 2) cec09 unconstrained test instances [4], as compared to the state-of-the-art EMO methods, MOEA/D only and NSGA-II only.