A multimethod search approach based on adaptive generations level

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 and NSGA-II 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, 2) cec09 unconstrained test instances, as compared to the state-of-the-art EMO methods, MOEA/D only and NSGA-II only.