2008
DOI: 10.1007/s10845-008-0163-8
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Iterative flattening search for resource constrained scheduling

Abstract: Iterative Flattening Search (IFS) is a meta-heuristic strategy for solving multi-capacity scheduling problems. Given an initial solution, IFS iteratively applies: (1) a relaxationstep, in which a subset of scheduling decisions are randomly retracted from the current solution; and (2) a flattening-step, in which a new solution is incrementally recomputed from this partial schedule. Whenever a better solution is found, it is retained, and, upon termination, the best solution found during the search is returned. … Show more

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Cited by 14 publications
(5 citation statements)
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References 22 publications
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“…Resource envelope problems that provide upper and lower bounds on the resource utilization of consistent schedules of STNs are presented in (Kumar 2003). (Oddi et al 2010) applies Iterative Flattening Search, a meta-heuristic strategy, to resource-constrained scheduling problems. STNs with preferences on individual variables have been studied in (Kumar 2004) and (Kumar, Cirillo, and Koenig 2013).…”
Section: Discussionmentioning
confidence: 99%
“…Resource envelope problems that provide upper and lower bounds on the resource utilization of consistent schedules of STNs are presented in (Kumar 2003). (Oddi et al 2010) applies Iterative Flattening Search, a meta-heuristic strategy, to resource-constrained scheduling problems. STNs with preferences on individual variables have been studied in (Kumar 2004) and (Kumar, Cirillo, and Koenig 2013).…”
Section: Discussionmentioning
confidence: 99%
“…In this case, the procedure "C" is absent in the procedures "C"-"F"-"I"; the application of the "I" procedure is not appropriate; only the "F" procedure remains involved. Therefore the exploratory technique degenerates into an iterative gradient method [18][19][20][21][22][23][24]. Fig.…”
Section: Methodsmentioning
confidence: 99%
“…For a detailed description of the IFS see [10]. In this section, we describe IFS with changes needed to address our restrictions.…”
Section: Iterative Flattening Search and Modificationsmentioning
confidence: 99%
“…Since we relaxed the critical path, AONG can be compressed, and hence, some of the resource constraints may become faulty. Other possible strategies of choices of time constraints to remove push scheduling outside the local minimum can be found in [10].…”
Section: Iterative Flattening Search and Modificationsmentioning
confidence: 99%