Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/53148

TitleVariable neighborhood search for integrated planning and scheduling
Author(s)Leite, Mário
Alves, Cláudio
Pinto, Telmo
KeywordsHeuristics
Integrated optimization problems
Metaheuristics
Planning
Scheduling
Issue date2017
PublisherSpringer-Verlag
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract(s)In this paper, we consider the integrated planning and scheduling problem on parallel and identical machines. The problem is composed by two parts which are simultaneously solved in an integrated form. The first is the planning part, which consists in determining the jobs that should be processed in each period of time. The second is the scheduling part, which consists in assigning the jobs to the machines according to their release dates. We present new optimization approaches based on local search heuristics and metaheuristic methods based on variable neighborhood search using two neighborhood structures. Two different algorithms were implemented in the construction of initial solutions and combined with fifteen variants of the initial sequence of jobs. Computational experiments were performed with benchmark instances from the literature in order to assess the proposed methods.
TypeConference paper
URIhttp://hdl.handle.net/1822/53148
ISBN9783319623948
DOI10.1007/978-3-319-62395-5_49
ISSN0302-9743
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Livros e capítulos de livros/Books and book chapters

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