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Self-adaptive differential evolution algorithm using population size reduction and three strategies

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Abstract

Many real-world optimization problems are large-scale in nature. In order to solve these problems, an optimization algorithm is required that is able to apply a global search regardless of the problems’ particularities. This paper proposes a self-adaptive differential evolution algorithm, called jDElscop, for solving large-scale optimization problems with continuous variables. The proposed algorithm employs three strategies and a population size reduction mechanism. The performance of the jDElscop algorithm is evaluated on a set of benchmark problems provided for the Special Issue on the Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems. Non-parametric statistical procedures were performed for multiple comparisons between the proposed algorithm and three well-known algorithms from literature. The results show that the jDElscop algorithm can deal with large-scale continuous optimization effectively. It also behaves significantly better than other three algorithms used in the comparison, in most cases.

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Notes

  1. DECC-G*: the same as DECC-G, except that the grouping structure was used as prior knowledge. The parameter group size was set to s = 50. The adaptive weighting strategy of DECC-G was not used.

  2. It is interesting to note that the results obtained on the test suite by using DE/rand/1/exp strategy are clearly better than those obtained by employing the DE/rand/1/bin strategy.

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Acknowledgments

The authors would like to thank the organizers of this special issue and the reviews for their valuable comments.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ulica 17, 2000, Maribor, Slovenia

    Janez Brest & Mirjam Sepesy Maučec

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  1. Janez Brest
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  2. Mirjam Sepesy Maučec
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Correspondence to Janez Brest.

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This work was supported in part by the Slovenian Research Agency under programs P2-0041 and P2-0069.

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Brest, J., Maučec, M.S. Self-adaptive differential evolution algorithm using population size reduction and three strategies. Soft Comput 15, 2157–2174 (2011). https://doi.org/10.1007/s00500-010-0644-5

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