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Parallel machine scheduling with flexible resources
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AI
DOI：10.1016/j.cie.2012.03.018.png)
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Abstract
En 中文
Parallel machine flexible resource scheduling (PMFRS) problems consider an additional flexible resource (e.g. operators), which can be freely allocated to any jobs and/or any machines and may speed-up the process in proportion to its amount. If job-machine assignment is unspecified, the problem is referred to as unspecified PMFRS (UPMFRS). This paper reviews the mathematical models of both PMFRS and UPMFRS problems in the literature and not only gives some extensions to the model of dynamic PMFRS problem but also presents integer programming (IP) models for static and dynamic UPMFRS problems with the objective of minimizing makespan. To solve large-sized dynamic PMFRS and UPMFRS problems, a relaxed IP based constraint programming (CP) approach is also proposed. All IP models and the proposed IP/CP approach are tested with an extensive computational study. The results of the computational experiments are discussed with respect to the major parameters of the problem and conclusions are drawn. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Parallel machines
Flexible resources
Scheduling
Integer programming
Constraint programming
Journal
IF:
6.5
Papers:
1.0W
Citations:
3.8W