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A Note on Bound Constraints Handling for the IEEE CEC'05 Benchmark Function Suite

机译:关于IEEE CEC'05基准功能套件的约束约束处理的说明

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The benchmark functions and some of the algorithms proposed for the special session on real parameter optimization of the 2005 IEEE Congress on Evolutionary Computation (CEC'05) have played and still play an important role in the assessment of the state of the art in continuous optimization. In this article, we show that if bound constraints are not enforced for the final reported solutions, state-of-the-art algorithms produce infeasible best candidate solutions for the majority of functions of the IEEE CEC'05 benchmark function suite. This occurs even though the optima of the CEC'05 functions are within the specified bounds. This phenomenon has important implications on algorithm comparisons, and therefore on algorithm designs. This article's goal is to draw the attention of the community to the fact that some authors might have drawn wrong conclusions from experiments using the CEC'05 problems.
机译:在2005年IEEE进化计算大会(CEC'05)的实际参数优化特别会议上提出的基准函数和一些算法在持续优化的技术水平评估中一直发挥着重要作用。在本文中,我们表明,如果对最终报告的解决方案不施加约束,则最新算法将为IEEE CEC'05基准功能套件的大部分功能提供不可行的最佳候选解决方案。即使CEC'05函数的最佳值在指定范围内,也会发生这种情况。这种现象对算法比较具有重要意义,因此对算法设计也具有重要意义。本文的目的是引起社区的注意,即某些作者可能从使用CEC'05问题的实验中得出了错误的结论。

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