NILS：一种基于中性的迭代局部搜索算法及其在Flowshop调度中的应用
NILS: a Neutrality-based Iterated Local Search and its application to Flowshop Scheduling
摘要：
本文提出了一种新的方法，利用健身景观的具体特点。特别是，我们对中立性属性感兴趣，它涉及这样一个事实：相同的适应度值被分配给来自搜索空间的许多解。许多组合优化问题都具有这一特性，这对局部搜索算法是非常不利的。提出了一种基于中性的迭代局部搜索算法，该算法允许中性步在平台上移动，并以最小化最大完工时间为目标，在置换流水车间调度问题上进行了实验。我们的实验表明，所提出的方法是能够找到改进的解决方案相比，经典的迭代局部搜索。此外，深入分析了利用中立性和探索搜索空间的新部分之间的权衡。
英文摘要：
This paper presents a new methodology that exploits specific characteristics from the fitness landscape. In particular, we are interested in the property of neutrality, that deals with the fact that the same fitness value is assigned to numerous solutions from the search space. Many combinatorial optimization problems share this property, that is generally very inhibiting for local search algorithms. A neutrality-based iterated local search, that allows neutral walks to move on the plateaus, is proposed and experimented on a permutation flowshop scheduling problem with the aim of minimizing the makespan. Our experiments show that the proposed approach is able to find improving solutions compared with a classical iterated local search. Moreover, the tradeoff between the exploitation of neutrality and the exploration of new parts of the search space is deeply analyzed.
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。
