用自适应松弛规则处理群算法中的等式约束
Handling equality constraints by adaptive relaxing rule for swarm algorithms
摘要：
针对群算法处理等式约束问题，提出了自适应约束松弛规则。这类问题的可行空间可能类似于岭函数类，这给群算法的应用带来了困难。为了更容易进入解空间，引入了松弛拟可行空间，并自适应收缩。在基准函数上的实验结果与其他算法的性能进行了比较，证明了该算法的有效性。
英文摘要：
The adaptive constraints relaxing rule for swarm algorithms to handle with the problems with equality constraints is presented. The feasible space of such problems may be similiar to ridge function class, which is hard for applying swarm algorithms. To enter the solution space more easily, the relaxed quasi feasible space is introduced and shrinked adaptively. The experimental results on benchmark functions are compared with the performance of other algorithms, which show its efficiency.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
