Abstract
Our article aims to resolve the scheduling instances in a job shop, hereinafter referred to as JSSP. The objective is to minimize the makespan, or the maximum amount of time needed to complete all tasks. In this contribution, we study an improved hybrid metaheuristic for solving active scheduling. This hybrid metaheuristic improves the outcome based on the previous output concerning some policies. The space solution is investigated using the local search algorithm by diversifying the neighborhood structure. The new matrix heuristic is used to design an admissible schedule and evaluate the makespan of the neighbor of the present solution.Benchmark instances are simulated using MATLAB to evaluate the efficiency of our metaheuristic. The new metaheuristic is quick to compute, straightforward, and simple to use. Comparative studies between different neighborhoods used by our metaheuristic, emphasize that using the hybrid's combination of neighborhoods gives the best results. The results’ simulations demonstrate the quality of the suggested metaheuristic.
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