Integrated heuristics for scheduling multiple order jobs in a complex job shop

Authors:
Jagadish Jampani;Edward A. Pohl;Scott J. Mason;Lars Monch
Affiliations:
Dept of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR 72701, USA.;Dept of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR 72701, USA.;Dept of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR 72701, USA.;Dept of Mathematics and Computer Science, University of Hagen, 58097 Hagen, Germany
Venue:
International Journal of Metaheuristics
Year:
2010

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Abstract

Scheduling in semiconductor manufacturing involves numerous types of complexities, including assignment of orders to front-opening unified pods (FOUPs), assignment of FOUPs to batches, and batch processing on single or parallel machines in multiple tool-groups with re-entrant flows. Based on these features, wafer fabrication in semiconductor manufacturing is referred to as a complex job shop in the literature. Assignment of multiple customer orders to jobs/FOUPs and scheduling them in a complex job shop environment is labelled as MOJ-CJSSP (multiple orders per job complex job shop scheduling problem). In this paper, we present constraint programming (CP), ant colony optimisation (ACO), and integrated CP-ACO approaches to minimise the sum of weighted completion times of the orders in MOJ-CJSSP.