Abstract
It is well known that it is very difficult to solve constrained multiobjective optimization problems. Such problems not only need to optimize the objective function but also need to consider the constraints. The epsilon constraint handling method is commonly used, which releases the degree of constraint violations by defining a gradually decayed epsilon. However, for the solutions whose overall constraint violations degree is greater than epsilon, the original epsilon constraint handling method cannot guarantee the diversity of solutions and only constraint violations are considered. To solve this issue, this paper proposed an infeasible solutions diversity maintenance strategy for solutions whose constraint violations degree is greater than epsilon. The experimental results show that our proposed algorithm is very competitive with other state-of-the-art algorithms for constrained multiobjective optimization problems.
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Acknowledgements
The authors wish to thank the support of the National Natural Science Foundation of China (Grant No. 61876164, 61772178), the MOEA Key Laboratory of Intelligent Computing and Information Processing, the Science and Technology Plan Project of Hunan Province (Grant No. 2016TP1020), the Provinces and Cities Joint Foundation Project (Grant No. 2017JJ4001), Science and Technology Planning Project of Guangdong Province of China (Grant No. 2017B010111005), the Hunan province science and technology project funds (Grant No. 2018TP1036).
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Zhou, J., Zou, J., Zheng, J. et al. An infeasible solutions diversity maintenance epsilon constraint handling method for evolutionary constrained multiobjective optimization. Soft Comput 25, 8051–8062 (2021). https://doi.org/10.1007/s00500-021-05880-5
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DOI: https://doi.org/10.1007/s00500-021-05880-5