Abstract
In this paper, we address the integrated planning and scheduling problem on parallel machines in which a set of jobs with release and due-dates have to be assigned first to consecutive time periods within the planning horizon, and then scheduled on the available machines. We explore in particular different alternative low complexity heuristics. The importance of job sequencing in the performance of these heuristics is analyzed, and a new property characterizing the optimal solutions of the problem is described. We also present a heuristic that yields optimal solutions for specific instances of the problem, and local exchange procedures that proved to be effective. To the best of our knowledge, these are the first contributions concerning the heuristic solution of this integrated planning and scheduling problem through low complexity procedures. To evaluate performance of these heuristics, we report on extensive computational experiments on benchmark instances of the literature.
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Rietz, J., Alves, C., de Carvalho, J.V. (2015). Fast Heuristics for Integrated Planning and Scheduling. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9156. Springer, Cham. https://doi.org/10.1007/978-3-319-21407-8_30
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DOI: https://doi.org/10.1007/978-3-319-21407-8_30
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