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The use of metaheuristics to software project scheduling problem

dc.contributor.authorCrawford B.
dc.contributor.authorSoto R.
dc.contributor.authorJohnson F.
dc.contributor.authorMisra S.
dc.contributor.authorParedes F.
dc.date.accessioned2020-09-02T22:15:38Z
dc.date.available2020-09-02T22:15:38Z
dc.date.issued2014
dc.identifier10.1007/978-3-319-09156-3_16
dc.identifier.citation8583 LNCS, PART 5, 215-226
dc.identifier.issn03029743
dc.identifier.urihttps://hdl.handle.net/20.500.12728/4135
dc.descriptionThis paper provides an overview of Software Project Scheduling problem as a combinatorial optimization problem. Since its inception by Alba, there have been multiple models to solve this problem. Metaheuristics provide high-level strategies capable of solving these problems efficiently. A set of metaheuristics used to solve this problem is presented, showing the resolution structure and its application. Among these we can find Simulated Annealing, Variable Neighborhood Search, Genetic Algorithms, and Ant Colony Optimization. © 2014 Springer International Publishing.
dc.language.isoen
dc.publisherSpringer Verlag
dc.subjectMetaheuristcs
dc.subjectOptimization
dc.subjectSoftware Project Scheduling
dc.subjectCombinatorial optimization
dc.subjectGenetic algorithms
dc.subjectHeuristic algorithms
dc.subjectOptimization
dc.subjectScheduling
dc.subjectSimulated annealing
dc.subjectCombinatorial optimization problems
dc.subjectITS applications
dc.subjectMeta heuristics
dc.subjectMetaheuristcs
dc.subjectResolution structure
dc.subjectSoftware Project Scheduling
dc.subjectVariable neighborhood search
dc.subjectProblem solving
dc.titleThe use of metaheuristics to software project scheduling problem
dc.typeConference Paper


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