<![CDATA[The issue of energy consumption is currently a major concern globally, especially in the industrial sector, where most of the energy demand comes from the manufacturing sector. To reduce energy consumption, one of the proposed strategies is to reduce the idle time between jobs on machines during the production process, known as No-Idle Permutation Flowshop Scheduling (NIPFSP). This research proposes the application of the African Vultures Optimization Algorithm (AVOA) as a solution to the energy consumption challenge in the case of production scheduling. The algorithm is examined in detail through a series of trials to obtain the most efficient work order in the production schedule, subject to careful setting of iteration and population parameters. The result of implementing the AVOA algorithm is then compared with the method used by the company in a scheduling case. The research findings show that AVOA significantly outperforms the method commonly used by the company, confirming its performance advantage in optimizing energy consumption in the context of production scheduling.]]>
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