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A local multiobjective optimization algorithm using neighborhood field

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Abstract

A new local search algorithm for multiobjective optimization problems is proposed to find the global optima accurately and diversely. This paper models the cooperatively local search as a potential field, which is called neighborhood field model (NFM). Using NFM, a new Multiobjective Neighborhood Field Optimization (MONFO) algorithm is proposed. In MONFO, the neighborhood field can drive each individual moving towards the superior neighbor and away from the inferior neighbor. MONFO is compared with other popular multiobjective algorithms under twelve test functions. Intensive simulations show that MONFO is able to deliver promising results in the respects of accuracy and diversity, especially for multimodal problems.

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  1. Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China

    Zhou Wu & Tommy W. S. Chow

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  1. Zhou Wu
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  2. Tommy W. S. Chow
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Correspondence to Tommy W. S. Chow.

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Wu, Z., Chow, T.W.S. A local multiobjective optimization algorithm using neighborhood field. Struct Multidisc Optim 46, 853–870 (2012). https://doi.org/10.1007/s00158-012-0800-x

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