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Heuristics, Metaheuristics and Approximate Methods in by Ghaith Rabadi (eds.)

By Ghaith Rabadi (eds.)

The scope of this ebook is proscribed to heuristics, metaheuristics, and approximate equipment and algorithms as utilized to making plans and scheduling difficulties. whereas it's not attainable to provide a entire therapy of this subject in a single publication, the purpose of this paintings is to supply the reader with a various set of making plans and scheduling difficulties and various heuristic ways to resolve them. the issues variety from conventional unmarried degree and parallel desktop difficulties to extra smooth settings reminiscent of robot cells and versatile task store networks. additionally, a few chapters take care of deterministic difficulties whereas a few others deal with stochastic models of the issues. in contrast to many of the literature that offers with making plans and scheduling difficulties within the production and construction environments, during this booklet the environments have been prolonged to nontraditional purposes corresponding to spatial scheduling (optimizing area over time), runway scheduling, and surgical scheduling. the answer tools utilized in different chapters of the ebook additionally unfold from well-established heuristics and metaheuristics akin to Genetic Algorithms and Ant Colony Optimization to newer ones resembling Meta-RaPS.

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Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling

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Uzsoy ( ) Edward P. edu © Springer International Publishing Switzerland 2016 G. -C. Lin and R. Uzsoy available may disrupt supporting activities such as staffing, material procurement, and machine setup that are initiated based on plans developed in earlier periods. This phenomenon, referred to in the literature as schedule nervousness or stability, has been addressed by many researchers over the last several decades (Mather 1977; Carlson et al. 1979; Blackburn et al. 1985, 1986; Sridharan et al.

It is intuitive that a sufficiently high unit release change cost should completely eliminate all release changes; a release cost of infinity corresponds to a constraint setting all planned release changes to zero. Setting the unit cost of positive release changes higher than the backlog cost will drive the primal model presented in Sect. 3 to hold backlogs instead of modifying releases. Negative release changes, on the other hand, may be eliminated by adjusting the associated change costs 2 Estimating the Costs of Planned Changes Implied by Freezing Production Plans 31 relative to the unit FGI and WIP holding costs, causing the model to hold inventory instead of reducing releases.

Uzsoy Fig. 2 Example of freezing the schedule based on demand information outside the current planning window. The red cells labelled (F) indicate the periods we decide to freeze. For example, as Fig. 2a shows, when we freeze the release plan in period s C 2 in epoch s, we also need to freeze periods s and s C 1 prior to it which are labelled (E). In the next epoch s C 1 as shown in Fig. 2b, we will freeze period s C 3 and all periods prior to it in the current planning epoch. 4 Behavior of Positive and Negative Release Changes In this section, we analyze the causes of release changes and how they affect the production system.

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