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- W1504307235 abstract "In a multimodal optimization task, the main purpose is to find multiple optimal solutions, so that the user can have a better knowledge about different optimal solutions in the search space and as and when needed, the current solution may be replaced by another optimum solution. Recently, we proposed a novel and successful evolutionary multi-objective approach to multimodal optimization. Our work however made use of three different parameters which had to be set properly for the optimal performance of the proposed algorithm. In this paper, we have eliminated one of the parameters and made the other two self-adaptive. This makes the proposed multimodal optimization procedure devoid of user specified parameters (other than the parameters required for the evolutionary algorithm). We present successful results on a number of different multimodal optimization problems of upto 16 variables to demonstrate the generic applicability of the proposed algorithm." @default.
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- W1504307235 date "2010-01-01" @default.
- W1504307235 modified "2023-09-25" @default.
- W1504307235 title "A Bi-criterion Approach to Multimodal Optimization: Self-adaptive Approach" @default.
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- W1504307235 doi "https://doi.org/10.1007/978-3-642-17298-4_10" @default.
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