TY - JOUR
T1 - Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times
AU - Mönch, Lars
AU - Balasubramanian, Hari
AU - Fowler, John
AU - Pfund, Michele E.
N1 - Funding Information:
The authors gratefully acknowledge the support of International SEMATECH and the Semiconductor Research Corporation through the Factory Operations Research Center (FORCe) project 2001-NJ-880. The authors would like to thank Jeaninne Schmidt for fruitful discussions and her valuable programming and testing efforts. Parts of this research were carried out while the first author was visiting the Modeling and Analysis of Semiconductor Manufacturing (MASM) Laboratory at Arizona State University.
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2005/11
Y1 - 2005/11
N2 - This research is motivated by a scheduling problem found in the diffusion and oxidation areas of semiconductor wafer fabrication, where the machines can be modeled as parallel batch processors. We attempt to minimize total weighted tardiness on parallel batch machines with incompatible job families and unequal ready times of the jobs. Given that the problem is NP-hard, we propose two different decomposition approaches. The first approach forms fixed batches, then assigns these batches to the machines using a genetic algorithm (GA), and finally sequences the batches on individual machines. The second approach first assigns jobs to machines using a GA, then forms batches on each machine for the jobs assigned to it, and finally sequences these batches. Dispatching and scheduling rules are used for the batching phase and the sequencing phase of the two approaches. In addition, as part of the second decomposition approach, we develop variations of a time window heuristic based on a decision theory approach for forming and sequencing the batches on a single machine.
AB - This research is motivated by a scheduling problem found in the diffusion and oxidation areas of semiconductor wafer fabrication, where the machines can be modeled as parallel batch processors. We attempt to minimize total weighted tardiness on parallel batch machines with incompatible job families and unequal ready times of the jobs. Given that the problem is NP-hard, we propose two different decomposition approaches. The first approach forms fixed batches, then assigns these batches to the machines using a genetic algorithm (GA), and finally sequences the batches on individual machines. The second approach first assigns jobs to machines using a GA, then forms batches on each machine for the jobs assigned to it, and finally sequences these batches. Dispatching and scheduling rules are used for the batching phase and the sequencing phase of the two approaches. In addition, as part of the second decomposition approach, we develop variations of a time window heuristic based on a decision theory approach for forming and sequencing the batches on a single machine.
KW - Batching
KW - Genetic algorithms
KW - Parallel machines
KW - Scheduling
KW - Semiconductor manufacturing
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U2 - 10.1016/j.cor.2004.04.001
DO - 10.1016/j.cor.2004.04.001
M3 - Article
AN - SCOPUS:13844256873
SN - 0305-0548
VL - 32
SP - 2731
EP - 2750
JO - Computers and Operations Research
JF - Computers and Operations Research
IS - 11
ER -