New model and heuristics for safety stock placement in general acyclic supply chain networks

We model the safety stock placement problem in general acyclic supply chain networks as a project scheduling problem, for which the constraint programming (CP) techniques are both effective and efficient in finding high quality solutions. We further integrate CP with a genetic algorithm (GA), which...

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Bibliographic Details
Published inComputers & operations research Vol. 39; no. 7; pp. 1333 - 1344
Main Authors Li, Haitao, Jiang, Dali
Format Journal Article
LanguageEnglish
Published New York Elsevier Ltd 01.07.2012
Pergamon Press Inc
Subjects
Constraint programming (CP)
General acyclic network
Genetic algorithm (GA)
Genetic algorithms
Heuristic
Inventory management
Inventory positioning
Mathematical models
Mathematical programming
Networks
Optimization
Placement
Production scheduling
Programming
Project scheduling
Safety stock placement
Safety stocks
Studies
Supply chain management
Supply chains
Inventory positioning
Genetic algorithm (GA)
Project scheduling
Constraint programming (CP)
General acyclic network
Safety stock placement
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Summary:We model the safety stock placement problem in general acyclic supply chain networks as a project scheduling problem, for which the constraint programming (CP) techniques are both effective and efficient in finding high quality solutions. We further integrate CP with a genetic algorithm (GA), which improves the CP solution quality significantly. The performance of our hybrid CP–GA algorithm is evaluated on randomly generated test instances. CP–GA is able to find optimal solutions to small problems in fractions of a second, and near optimal solutions of about 5% optimality gap to medium size problems in several minutes on average.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2011.08.001