Paper Info
Title
Metaheuristics for scheduling jobs with incompatible families on parallel batching machines.
Abstract
In this paper, we discuss the scheduling of jobs with incompatible families on parallel batching machines. The performance measure is total weighted tardiness. This research is motivated by a scheduling problem found in the diffusion and oxidation areas of semiconductor wafer fabrication where the machines can be modelled as parallel batch processors. Given that this scheduling problem is NP-hard, we suggest an ant colony optimization (ACO) and a variable neighbourhood search (VNS) approach. Both metaheuristics are hybridized with a decomposition heuristic and a local search scheme. We compare the performance of the two algorithms with that of a genetic algorithm (GA) based on extensive computational experiments. The VNS approach outperforms the ACO and GA approach with respect to time and solution quality. Journal of the Operational Research Society (2011) 62, 2083-2096. doi: 10.1057/jors.2010.186 Published online 29 December 2010
Year
DOI
Venue
2011
10.1057/jors.2010.186
JORS
Keywords
Field
DocType
operational research,scheduling,management science,location,marketing,local search,investment,production,communications technology,genetic algorithm,computer science,inventory,ant colony optimization,information systems,operations research,logistics,information technology,reliability,forecasting,scheduling problem,project management,computer experiment
Ant colony optimization algorithms,Heuristic,Job shop scheduling,Tardiness,Computer science,Scheduling (computing),Local search (optimization),Genetic algorithm,Operations management,Metaheuristic
Journal
Volume
Issue
ISSN
62
12
0160-5682
Citations 
PageRank 
References 
16
0.71
20
Authors
2
Name
Order
Citations
PageRank
Christian Almeder1907.09
Lars Mönch21034124.98