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An infeasible solutions diversity maintenance epsilon constraint handling method for evolutionary constrained multiobjective optimization
Soft Computing ( IF 3.1 ) Pub Date : 2021-05-25 , DOI: 10.1007/s00500-021-05880-5
Jinlong Zhou , Juan Zou , Jinhua Zheng , Shengxiang Yang , Dunwei Gong , Tingrui Pei

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.



中文翻译:

进化约束多目标优化的不可行解多样性维护epsilon约束处理方法

众所周知,求解受约束的多目标优化问题非常困难。此类问题不仅需要优化目标函数,还需要考虑约束条件。常用的是epsilon约束处理方法,通过定义一个逐渐衰减的epsilon来释放约束违反的程度。但是,对于整体约束违反程度大于epsilon的解,原有的epsilon约束处理方法不能保证解的多样性,只考虑约束违反。针对这一问题,本文针对约束违反程度大于epsilon的解提出了不可行解多样性维护策略。

更新日期:2021-06-14
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