| Summary: | Flow shop scheduling is crucial in manufacturing and production environments because it directly impacts output and overall production efficiency. It involves processing a set of jobs on multiple machines in a specific order. The objective is to determine the optimal job sequence that minimizes the makespan, which is the total time required to complete all jobs. This study proposes a computerized approach utilizing the Whale Optimization Algorithm (WOA) to solve the flow shop scheduling problem and minimize the makespan. The WOA is a recently developed meta-heuristic algorithm inspired by the bubble-net hunting strategy of humpback whales. The performance of the WOA is evaluated using five benchmark problems with varying numbers of jobs and machines, and the results are compared with those obtained from other algorithms reported in the literature, such as genetic algorithms and heuristic models. The findings demonstrate that the WOA can effectively solve the flow shop scheduling problem and provide improved makespan values, with an average efficiency of 7.33% compared to the other algorithms.
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