A linear programming-based method for job shop scheduling
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We present a decomposition heuristic for a large class of job shop scheduling problems. This heuristic utilizes information from the linear programming formulation of the associated optimal timing problem to solve subproblems, can be used for any objective function whose associated optimal timing problem can be expressed as a linear program (LP), and is particularly effective for objectives that include a component that is a function of individual operation completion times. Using the proposed heuristic framework, we address job shop scheduling problems with a variety of objectives where intermediate holding costs need to be explicitly considered. In computational testing, we demonstrate the performance of our proposed solution approach.
KeywordsJob shop Shifting bottleneck Intermediate inventory holding costs Non-regular objective Optimal timing problem Linear programming Sensitivity analysis Single machine Earliness/tardiness
- Asadathorn, N. (1997). Scheduling of assembly type of manufacturing systems: algorithms and systems developments. PhD thesis, Department of Industrial Engineering, New Jersey Institute of Technology, Newark, NJ. Google Scholar
- Avci, S., & Storer, R. (2004). Compact local search neighborhoods for generalized scheduling. Working paper. Google Scholar
- Bulbul, K. (2002). Just-in-time scheduling with inventory holding costs. PhD thesis, University of California at Berkeley. Google Scholar
- Chang, Y. L., Sueyoshi, T., & Sullivan, R. (1996). Ranking dispatching rules by data envelopment analysis in a jobshop environment. IIE Transactions, 28(8), 631–642. Google Scholar
- Kaskavelis, C., & Caramanis, M. (1998). Efficient Lagrangian relaxation algorithms for industry size job-shop scheduling problems. IIE Transactions, 30(11), 1085–1097. Google Scholar
- LEKIN®-Flexible Job-Shop Scheduling System (2002). Version 2.4. http://www.stern.nyu.edu/om/software/lekin/index.htm.
- Ovacik, I. M., & Uzsoy, R. (1996). Decomposition methods for complex factory scheduling problems. Berlin: Springer. Google Scholar
- Xhafa, F., & Abraham, A. (Eds.) (2008). Studies in computational intelligence: Vol. 128. Metaheuristics for scheduling in industrial and manufacturing applications. Berlin: Springer. Google Scholar