Scheduling pp 431-458 | Cite as

Modeling and Solving Scheduling Problems in Practice

  • Michael L. Pinedo


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.


Schedule Problem Cycle Time Setup Time Feasible Schedule Sequence Dependent Setup Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.New York UniversityNew YorkUSA

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