The Jaya algorithm is arguably one of the fastest-emerging metaheuristics amongst the newest members of the evolutionary computation family. The present paper proposes a new, improved Jaya algorithm by modifying the update strategies of the best and the worst members in the population. Simulation results on a twelve-function benchmark test-suite as well as a real-world problem of practical importance show that the proposed strategy produces results that are better and faster in the majority of cases. Statistical tests of significance are used to validate the performance improvement.

中文翻译：

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半稳态 Jaya 算法

Jaya 算法可以说是进化计算家族的最新成员中出现最快的元启发式算法之一。本文通过修改种群中最好和最差成员的更新策略，提出了一种新的、改进的 Jaya 算法。十二功能基准测试套件的模拟结果以及具有实际重要性的现实问题表明，所提出的策略在大多数情况下产生的结果更好更快。显着性统计检验用于验证性能改进。