论文标题
全球本地社区搜索算法和禁忌搜索灵活的车间调度问题
A global-local neighborhood search algorithm and tabu search for flexible job shop scheduling problem
论文作者
论文摘要
灵活的车间调度问题（FJSP）是一个组合问题，由于其在制造系统和新出现的新变体中的实际含义，因此继续进行了广泛的研究，以建模和优化更复杂的情况，以反映出该行业的当前需求。这项工作提出了一种称为GLNSA（全局邻里搜索算法）的新的元元素算法，其中使用了蜂窝自动机的邻域概念，因此一组称为“ Smart_Cells”的领先解决方案会生成并共享有助于FJSP实例的信息。 GLNSA算法与禁忌搜索相辅相成，该搜索实现了[1]中定义的NOPT1邻域的简化版本，以补充优化任务。进行的实验表明，与最近在专业书目中发表的其他结果相比，该算法具有令人满意的性能，使用86个测试问题，改善了其中两个研究中的最佳结果。
The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new meta-heuristic algorithm called GLNSA (Global-local neighborhood search algorithm), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called "smart_cells" generates and shares information that helps to optimize instances of FJSP. The GLNSA algorithm is complemented with a tabu search that implements a simplified version of the Nopt1 neighborhood defined in [1] to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms and widely cited in the specialized bibliography, using 86 test problems, improving the optimal result reported in previous works in two of them.
