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The m-Machine Flow Shop

Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 182)

Abstract

Considered to be a very general case of flow shop systems, the m-machine flow shop is the most researched system in all of flow shop theory. Beyond solving the problem under a variety of objectives and side constraints, the m-machine flow shop serves as a test bed for new methodological tools. Regarding solutions, the research presented in this chapter is rich in lower bounding schemes, dominance properties, heuristic algorithms and computational experiments measuring their success. The models considered not only deal with all the standard regular performance measures, but also application-specific objective functions. A lot of work is also available on problems with multiple objectives. We find that the most successful solutions on problems of practical size are due to metaheuristic implementations including simulated annealing, tabu search and genetic algorithms. In contrast, branch-and-bound algorithms are mostly inadequate.

Keywords

Schedule Problem Completion Time Flow Shop Total Tardiness Partial Schedule 
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 New York 2013

Authors and Affiliations

  1. 1.Weatherhead School of ManagementCase Western Reserve UniversityClevelandUSA

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