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Memetic Computing

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26-07-2020 | Regular Research Paper

Hybrid many-objective cuckoo search algorithm with Lévy and exponential distributions

Authors: Zhihua Cui, Maoqing Zhang, Hui Wang, Xingjuan Cai, Wensheng Zhang, Jinjun Chen

Published in: Memetic Computing | Issue 3/2020

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Abstract

Hybrid many-objective cuckoo search algorithm (HMaOCS) is a newly proposed method for Many-objective optimization problems (MaOPs), and has achieved promising performance. However, Lévy and Gaussian distributions used in global search manner of HMaOCS is originally proposed for optimization problems with one objective, and they are not suitable for MaOPs as illustrated in this paper. To further exploit the potential of HMaOCS, this paper investigates four different probability distributions and their six corresponding combinations. Comparison results illustrate that the combination of Lévy and Exponential distributions is able to greatly improve HMaOCS. On the basis of comparison results and analysis on both DTLZ and WFG test suites with 2, 3, 4, 6, 8 and 10 objectives, it can be concluded that HMaOCS with Lévy and Exponential distributions exhibits better performance compared with most advanced algorithms.

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Zhang M, Wang H, Cui Z, Chen J (2018) Hybrid multi-objective cuckoo search with dynamical local search. Memet Comput 10(2):199–208CrossRef

Rostami S, Neri F, Epitropakis M (2017) Progressive preference articulation for decision making in multi-objective optimisation problems. Integr Comput-Aided Eng 24(4):315–335CrossRef

Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evolut Comput 6(2):182–197CrossRef

Coello Coello C A, Lechuga M S(2002) MOPSO: A proposal for multiple objective particle swarm optimization. In: Proceedings of the IEEE congress on evolutionary computation, pp 1051–1056

Rostami S, Neri F (2016) Covariance matrix adaptation pareto archived evolution strategy with hyper volume-sorted adaptive grid algorithm. Integr Comput Aided Eng 23(4):313–329CrossRef

Deb K, Jain H (2014) An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, part I: Solving problems with box constraints. IEEE Trans Evolut Comput 18(4):577–601CrossRef

Rostami S, Neri F (2017) A fast hypervolume driven selection mechanism for many-objective optimisation problems. Swarm Evolut Comput 34:50–67CrossRef

Zhang Q, Li H (2007) MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evolut Comput 11(6):712–731CrossRef

Yang S, Li M, Liu X, Zheng J (2013) A grid-based evolutionary algorithm for many-objective optimization. IEEE Trans Evolut Comput 17(5):721–736CrossRef

10.

Zhang X, Tian Y, Jin Y (2015) A knee point-driven evolutionary algorithm for many-objective optimization. IEEE Trans Evolut Comput 19(6):761–776CrossRef

11.

Laumanns M, Thiele L, Deb K, Zitzler E (2002) Combining convergence and diversity in evolutionary multi-objective optimization. MIT Press, Cambridge, pp 263–282

12.

Zou X, Chen Y, Liu M, Kang L (2008) A new evolutionary algorithm for solving many-objective optimization problems. IEEE Trans Syst Man Cybern Part B Cybern 38(5):1402–1412CrossRef

13.

Zitzler E, Kunzli S (2004) Indicator-based selection in multiobjective search. In: Proceedings of the international conference on parallel problem solving from nature, pp 832–842

14.

Bader J, Zitzler E (2011) HypE: an algorithm for fast hypervolume-based many-objective optimization. Evolut Comput 19(1):45–76CrossRef

15.

Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans Evolut Comput 3(4):257–271CrossRef

16.

Nebro A J, Durillo J J, Garcia-Nieto J, Coello Coello CA, Luna F, Alba E (2009) SMPSO: a new PSO-based metaheuristic for multi-objective optimization. In: Proceedings of the IEEE symposium on computational intelligence in multi-criteria decision-making, pp 66–73

17.

Martinez SZ, Coello Coello CA (2011) A multi-objective particle swarm optimizer based on decomposition. In: Proceedings of the 13th annual conference on genetic and evolutionary computation, pp 69–76

18.

Okabe T, Jin Y, Sendhoff B (2004) Voronoi-based estimation of distribution algorithm for multi-objective optimization. In: IEEE congress on evolutionary computation 2004

19.

Bosman PAN, Thierens D (2005) The naive MIDEA: a baseline multi-objective EA. In: Proceedings of the third international conference on evolutionary multi-criterion optimization. Springer-Verlag

20.

Zhang Q, Zhou A, Jin Y (2008) RM-MEDA: a regularity model-based multiobjective estimation of distribution algorithm. IEEE Trans Evolut Comput 12(1):41–63CrossRef

21.

Yang XS, Deb S (2010) Cuckoo search via Lévy flights. In: Proceedings of world congress on nature and biologically inspired computing, India, pp 210–214

22.

Chandrasekaran K, Simon SP (2012) Multi-objective scheduling problem: hybrid approach using fuzzy assisted cuckoo search algorithm. Swarm Evolut Comput 5:1–12CrossRef

23.

Wu Z, Zhao X, Ma Y, Zhao Y (2019) A hybrid model based on modified multi-objective cuckoo search algorithm for short-term load forecasting. Appl Energy. https://doi.org/10.1016/j.apenergy.2019.01.046CrossRef

24.

Ruining Z, Xuemei J, Ruifang L (2018) Improved decomposition-based multi-objective cuckoo search algorithm for spectrum allocation in cognitive vehicular network. Phys Commun 2018:S1874490717303506

25.

Cui Z, Zhang M, Wang H, Cai X, Zhang W (2019) A hybrid many-objective Cuckoo search algorithm. Soft Comput. https://doi.org/10.1007/s00500-019-04004-4CrossRef

26.

Balasubbareddya M, Sivanagarajub S, Venkata Sureshc C (2017) A non-dominated Sorting Hybrid Cuckoo Search Algorithm for multi-objective optimization in the presence of FACTS devices. Rus Electr Eng 88(1):44–53CrossRef

27.

Wang Z, Li Y (2015) Irreversibility analysis for optimization design of plate fin heat exchangers using a multi-objective cuckoo search algorithm. Energy Convers Manag 101:126–135CrossRef

28.

Xiong W, Guo B, Shen Y (2018) A Discrete multi-objective optimization method for hardware/software partitioning problem based on cuckoo search and elite strategy. Neuroquantology 16(5):749–756CrossRef

29.

Cui Z, Sun B, Wang G (2016) A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber-physical systems. J Parallel Distrib Comput:S0743731516301393

Title: Hybrid many-objective cuckoo search algorithm with Lévy and exponential distributions
Authors: Zhihua Cui
Maoqing Zhang
Hui Wang
Xingjuan Cai
Wensheng Zhang
Jinjun Chen
Publication date: 26-07-2020
Publisher: Springer Berlin Heidelberg
Published in: Memetic Computing / Issue 3/2020
Print ISSN: 1865-9284
Electronic ISSN: 1865-9292
DOI: https://doi.org/10.1007/s12293-020-00308-3

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