论文标题
半态状态Jaya算法
Semi-steady-state Jaya Algorithm
论文作者
论文摘要
JAYA算法可以说是进化计算家族最新成员中最快的元启发式学之一。本文提出了一种新的，改进的Jaya算法，通过修改人口中最佳和最差成员的更新策略。模拟结果对十二个基准测试套件以及实际重要性的现实世界问题表明，所提出的策略在大多数情况下会产生更好，更快的结果。显着性统计检验用于验证性能的改善。
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.
