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Modeling and Solving Scheduling Problems in Practice

In: Scheduling

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  • Michael L. Pinedo

    (New York University)

Abstract

In Parts I and II a number of stylized and (supposedly) elegant mathematical models are discussed in detail. The deterministic models have led to a number of simple priority rules as well as to many algorithmic techniques and heuristic procedures. The stochastic models have provided some insight into the robustness of the priority rules. The results for the stochastic models have led to the conclusion that the more randomness there is in a system, the less advisable it is to use very sophisticated optimization techniques. Or, equivalently, the more randomness the system is subject to, the simpler the scheduling rules ought to be.

Suggested Citation

  • Michael L. Pinedo, 2012. "Modeling and Solving Scheduling Problems in Practice," Springer Books, in: Scheduling, edition 4, chapter 0, pages 431-458, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-2361-4_16
    DOI: 10.1007/978-1-4614-2361-4_16
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