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Cultural particle swarm optimization algorithms for uncertain multi-objective problems with interval parameters

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Abstract

Traditional dominant comparison never fits for uncertain multi-objective optimization problems with interval parameters. Moreover, existing particle swarm optimization algorithm for solving these uncertain optimization problems could not adaptively adjust the key parameters and easily fell into premature. To alleviate above weakness, a novel multi-objective cultural particle optimization algorithm is proposed. The highlights of this algorithm are: (i) The possibility degree is introduced to construct a novel dominant comparison relationship so as to rationally measure the uncertainty of particles; (ii) The grid’s coverage degree is defined based on topological knowledge and used to measure the uniformity of non-dominant solutions in objective space instead of the crowding distance. (iii) The key flight parameters are adaptively adjusted and the local or global best are selected in terms of the knowledge. The statistic simulation results for seven benchmark functions indicate that the solutions obtained from the proposed algorithms more close to the true Pareto front uniformly and the uncertainty of non-dominant solutions is less. Furthermore, the knowledge extracted from the evolution plays a rational impact on balancing exploration and exploitation.

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Acknowledgments

This work was supported in part by National Natural Science Foundation of China under Grant 61573361, Research Program of Frontier Discipline of China University of Mining and Technology under Grant 2015XKQY19, Outstanding innovation team of China University of Mining and Technology under Grant 2015QN003 and National Basic Research Program of China under Grant 2014CB046300.

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Authors and Affiliations

  1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, Jiangsu, China

    Yi-nan Guo, Zhen Yang, Chun Wang & Dunwei Gong

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  1. Yi-nan Guo
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  2. Zhen Yang
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  3. Chun Wang
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  4. Dunwei Gong
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Correspondence to Yi-nan Guo.

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Guo, Yn., Yang, Z., Wang, C. et al. Cultural particle swarm optimization algorithms for uncertain multi-objective problems with interval parameters. Nat Comput 16, 527–548 (2017). https://doi.org/10.1007/s11047-016-9556-3

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