SOLUTION APPROACHES FOR SIMULTANEOUS SCHEDULING OF JOBS AND OPERATORS ON PARALLEL MACHINES
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Abstract
In literature, most of the studies related to parallel machine scheduling problems assume that jobs require only machines as the processing resources and accordingly deal with simply job-machine scheduling problem. However, in real-life manufacturing environments, jobs may also require additional resources. A common example of additional resources is cross-training workers that perform tasks related with different machines. This study handles a real-life problem that requires simultaneous scheduling of jobs and operators over the parallel machines. Operators are responsible for monitoring the machines, unloading the parts and trimming extra material. These tasks may not require an operator's full attention during the processing of a job at one machine. In this context, a significant distinguishing feature of the investigated problem is that an operator can be assigned to more than one machine through the specified time periods. While determining the machines that an operator has to deal with during the same scheduling periods, the physical closeness of the machines should also be taken into account. For the problem on hand, with the aim of minimizing the completion time of the last job, integer and constraint programming models have been developed. The models have been evaluated through the test problems with different parameters, and their performances have been discussed. Finally, the applicability of the proposed constraint programming model on the real-life problem has been shown.