Heuristics for parallel-machine flexible-resource scheduling problems with unspecified job assignment

This paper considers a parallel-machine scheduling problem in which the operational impact of resource flexibility is explored through machine flexibility as well as labor flexibility. The main contribution of this paper is the identification of the existence of the problem in practice, the development of two efficient heuristics, and the comparison and analysis of the proposed heuristics. In this paper, we examine the parallel-machine flexible-resource scheduling problem in which job assignment to machines are not specified (UPMFRS). The UPMFRS problem is NP-hard, motivating the development of effective heuristics that approximately determine the job assignment to machines and the allocation of resources to jobs. The paper compares a decomposition heuristic and a tabu-search heuristic, and concludes that the tabu-search heuristic is cost and quality effective in locating the near-optimal solutions.