Metaheuristics for scheduling jobs with incompatible families on parallel batching machines

C Almeder and L Mönch ()
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C Almeder: Vienna University of Economics and Business
L Mönch: University of Hagen

Journal of the Operational Research Society, 2011, vol. 62, issue 12, 2083-2096

Abstract: 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.

Keywords: batching; scheduling; ant colony optimization; variable neighbourhood search; total weighted tardiness (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (4)

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DOI: 10.1057/jors.2010.186

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