In order to meet growing demands of the market modern manufacturing and service environments must offer an increasingly broad range of services or products as well as ensure their required amount and short lead times. It can be done by the application of universal machines or workers which are able to perform different tasks. On the other hand, human activity environments are often affected by learning. Therefore, in this paper, we analyse related problems, which can be expressed as the makespan minimization scheduling problem on identical parallel machines with variable setup times affected by learning of workers. To provide an efficient schedule, we propose metaheuristic algorithms. Their potential applicability is verified numerically.
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