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 metaheuristic algorithm called the global-local neighborhood search algorithm (GLNSA), 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 the FJSP. The GLNSA algorithm is accompanied by a tabu search that implements a simplified version of the Nopt1 neighborhood defined in Mastrolilli & Gambardella (2000) 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, using four benchmark sets and 101 test problems.

中文翻译：

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全局-局部邻域搜索算法和禁忌搜索，解决柔性作业车间调度问题

柔性作业车间调度问题（FJSP）是一个组合问题，由于其对制造系统和新兴的变体形式的实际影响，因此将继续进行广泛研究，以便对更复杂的情况进行建模和优化，以更好地反映行业的当前需求。这项工作提出了一种新的元启发式算法，称为全局局部邻域搜索算法（GLNSA），其中使用了细胞自动机的邻域概念，因此，一组称为智能单元的领先解决方案生成并共享有助于优化的信息。 FJSP的实例。GLNSA算法伴随着禁忌搜索，禁忌搜索实现了Mastrolilli＆Gambardella（2000）中定义的Nopt1邻域的简化版本，以补充优化任务。