Abstract
In this paper, we study the influence of machine maintenance to distributed scheduling problems. Distributed scheduling is aiming to maximize the system efficiency by simultaneously solving two problems: (i) allocation of jobs to suitable factories, and (ii) determination of the corresponding production scheduling in each factory. Scheduling of machine maintenance problems aim to reduce the effect of breakdown and maximize the facility availability at minimum cost. However, in many distributed scheduling problems, machine scheduling assumes that machines are available all the time. In fact, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it interrupts the production scheduling determined. This paper designed a hypothetical distributed scheduling model with three different problem sizes to demonstrate the significance of simultaneously solving machine maintenance problem with distributed scheduling problem. We applied genetic algorithm with dominant genes methodology to solve the model. Several optimization approaches, including separating and integrating the two problems, are tested and compared. The results show the merit of integration
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