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Growing Science » Management Science Letters » A novel modeling approach for job shop scheduling problem under uncertainty

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Management Science Letters
ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 3 Issue 11 pp. 2725-2736, 2013

A novel modeling approach for job shop scheduling problem under uncertainty Pages 2725-2736 Right click to download the paper Download PDF

Authors: Behnam Beheshti Pur, Siamak Noori, Reza Hosnavi Atashgah

📋 Author Affiliations:
Crossref Source: CrossRef

🔑 Keywords: Chance constrained programming (CCP), Expected utility programming (EUP), Simple recourse, Stochastic job shop scheduling problem (SJSSP), Utility theory

Abstract: When aiming on improving efficiency and reducing cost in manufacturing environments, production scheduling can play an important role. Although a common workshop is full of uncertainties, when using mathematical programs researchers have mainly focused on deterministic problems. After briefly reviewing and discussing popular modeling approaches in the field of stochastic programming, this paper proposes a new approach based on utility theory for a certain range of problems and under some practical assumptions. Expected utility programming, as the proposed approach, will be compared with the other well-known methods and its meaningfulness and usefulness will be illustrated via a numerical examples and a real case.

How to cite this paper
APA: Pur, B., Noori, S & Atashgah, R. (2013). A novel modeling approach for job shop scheduling problem under uncertainty. Management Science Letters, 3(11), 2725-2736.
Chicago/Turabian: Pur, B., Noori, S & Atashgah, R. 2013. "A novel modeling approach for job shop scheduling problem under uncertainty." Management Science Letters 3, no. 11 (2013): 2725-2736.
AMA: Pur, B., Noori, S & Atashgah, R. A novel modeling approach for job shop scheduling problem under uncertainty. Management Science Letters. 2013;3(11):2725-2736.

References
Alves, M. J. & Almeida, M. (2007). MOTGA: A multiobjective Tchebycheff based genetic algorithm for the multidimensional knapsack problem. Computers and Operations Research, 34, 3458 – 3470.

Anscombe, F. & Aumann, R. J. (1963). A definition of subjective probability. Annals of Mathematical Statistics, 34, 199–205.

Baker, K. R. & Trietsch , D. (2009). Principles of Sequencing and Scheduling. John Wiley & Sons, Hoboken, New Jersey.

Birge, J.R., & Louveaux, F. (1997). Introduction to Stochastic Programming. Springer, New York.
Brucker, P. (2007). Scheduling Algorithms. Springer, Berlin.

Charnes, A. & Cooper, W.W. (1959). Chance-constrained programming. Management Science, 6, 73–79.

Cheng, R., Gen, M., & Tsujimura, Y. (1996). A tutorial survey of job-shop scheduling problems using genetic algorithms. Computers & Industrial Engineering, 30(4), 983–997.

Feller, W. (1950). An Introduction to Probability Theory and Its Applications. Vol. 1. John Wiley & Sons, New York.

Friedman, M., & Savage, L. J. (1948). The utility analysis of choices involving risk. Journal of Political Economy, 56, 279–304.

Ghorbani, S. & Rabbani, M. (2009). A new multi-objective algorithm for a project selection problem. Advances in Engineering Software, 40, 9–14.

Gintis, H. (2009). Game Theory Evolving, 2nd Ed. Princeton University Press, Princeton.

Gonçalvesa, J. F., Mendes, J. J. M., & Resende, M. G. C. (2005). A hybrid genetic algorithm for the job shop scheduling problem. European Journal of Operational Research, 167 (1), 77–95.

Gourgand, M., Grangeon, N., & Norre, S. (2003). A contribution to the stochastic flow shop scheduling problem. European Journal of Operational Research, 151(2), 415 –33.

Gu, M. & Lu, X. (2009). Preemptive stochastic online scheduling on two uniform machines. Information Processing Letters, 109, 369–75.

Gua, J., Gub, M., Caoa, C., & Gu, X. (2010). A novel competitive co-evolutionary quantum genetic algorithm for stochastic job shop scheduling problem. Computers & Operations Research, 37, 927 - 937.

Huang, R. (2010). Multi-objective job-shop scheduling with lot-splitting production. International Journal of Production Economics, 124, 206–213.

Lei, D. (2008). Pareto archive particle swarm optimization for multiobjective fuzzy job shop scheduling problems. International Journal of Advanced Manufacturing Technology, 37, 157–165.

Lenstra, J. K., Rinnooy Kan, A. H. G., & Brucker, P. (1977). Complexity of machine scheduling problems. Annals of Discrete Mathematics, 1, 343–362.

Lin, F. (2008). Solving the knapsack problem with imprecise weight coefficients using genetic algorithms. European Journal of Operational Research, 185, 133–145.

Li, Y.F., Xie, M., & Goh, T.N. (2009). A study of project selection and feature weighting for analogy based software cost estimation. Journal of Systems and Software, 82, 241–252.

Liu, B. (2007). Theory and Practice of Uncertain Programming. 2nd ed. Tsinghua University, Beijing.

Lopez, P. & Roubellat, F. (2008). Production Scheduling. John Wiley & Sons, Hoboken, New Jersey.
Neumann, V., Morgenstern, J. & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton University Press, Princeton.

Pezzellaa, F., Morgantia, G. & Ciaschetti, G. (2008). A genetic algorithm for the flexible job-shop scheduling problem. Computers & Operations Research, 35(10), 3202–3212.

Qian, B., Wang, L., Huang, D., & Wang, X. (2008). Scheduling multi-objective job shops using a memetic algorithm based on differential evolution. International Journal Advanced Manufacturing Technology, 35, 1014–1027.

Qing-dao-er-ji, R. & Wang, Y. (2012). A new hybrid genetic algorithm for job shop scheduling problem. Computers & Operations Research, 39(10), 2291–2299.

Savage, J. (1954). The Foundations of Statistics. John Wiley & Sons, New York.
Xhafa, F., & Abraham, A. (2008). Metaheuristics for Scheduling in Industrial and Manufacturing Applications. Springer, Berlin.

Yusof, R., Khalid, M., Teck Hui, G., Yusof, S. & Othman, M. (2011). Solving job shop scheduling problem using a hybrid parallel micro genetic algorithm. Applied Soft Computing, 11(8), 5782–5792.
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📚 Journal: Management Science Letters | 📅 Year: 2013 | 📖 Volume: 3 | 📄 Issue: 11 | 👁️ Views: 2198 | 📊 Crossref:

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