| Summary: | In industrial production management, production scheduling planning is a very important thing that aims to
optimize production time and costs to meet consumer needs and gain the maximum profit. During the production process,
other things also need to be considered, for instance, machine reliability. In addition, we assume that the production system
is in batch production. It means that we produce items in several groups with a variety of different specifications so that
each batch requires varying operational conditions in each process. Therefore, this paper proposes the optimization of
production and maintenance machine scheduling, taking into varying operational conditions on the pharmaceutical industry
in Central Java, Indonesia. We apply two methods to solve the problem, i.e., biased random key genetic and random key
genetic algorithms. Each method combined with the Jaya algorithm and convex set theory to obtain the optimal scheduling
results. The results show the total cost is different, but the total cost results obtained from the two methods are close
enough.
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