Wenting Mo

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This paper studies the strategies for multi-objective optimization in a dynamic environment. In particular, we focus on problems with objective replacement, where some objectives may be replaced with new objectives during evolution. It is shown that the Pareto-optimal sets before and after the objective replacement share some common members. Based on this(More)
In this paper, an evolutionary algorithm for multi-objective optimization problems in a dynamic environment is studied. In particular, we focus on decremental multi-objective optimization problems, where some objectives may be deleted during evolution-for such a process we call it as objective decrement. It is shown that the Pareto-optimal set after(More)
This paper presents a novel evolutionary approach for function optimization Incremental Evolution Strategy (IES). Two strategies are proposed. One is to evolve the input variables incrementally. The whole evolution consists of several phases and one more variable is focused in each phase. The number of phases is equal to the number of variables in maximum.(More)
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