<![CDATA[The current energy crisis is a pressing global challenge, with the industrial sector accounting for half of global energy consumption. Scheduling is considered one of the potential methods to reduce energy consumption. This article introduces the Fire Hawk Optimizer (FHO) algorithm to solve the no-idle flow shop scheduling problem to minimize overall energy consumption. FHO organizes the job sequence in no-idle flow shop scheduling for reduce energy consumption. This research investigates the use of different machine speed levels, namely slow, fast, and normal, based on case data of manufacturing industries in Indonesia. The results of this study compare the performance of the FHO algorithm with the Adaptive Integrated Greedy (AIG) heuristic method and compare it with the Grey Wolf Optimizer (GWO) algorithm. The experimental results showed that total energy consumption tends to be high when processed at high speed. Conversely, low-speed results in lower energy consumption but requires longer processing time. The comparison results show that the Fire Hawk Optimizer is more efficient in reducing total energy consumption than the AIG heuristic method. Meanwhile, the FHO algorithm performs comparably to the GWO algorithm and completes enumeration. These findings confirm that the proposed procedure can be an alternative to the scheduling optimization process.]]>
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