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Minimize Maximal Regret to Enhance Reliability in Flexible Open-Shop Problem

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Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA 2023)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1136))

Abstract

Within flexible manufacturing systems, scheduling and routing of products play a crucial role in the production chain. Therefore, it is essential to maintain acceptable performance levels by implementing intelligent product dispatching on machines, especially in the case of delayed processing time due to unforeseen events. This work examines a simplified version of a real production cell to assess whether using a minimax regret cost function can yield a valuable solution for solving the associated flexible open-shop scheduling problem under uncertain processing time. Results from a limited instance indicate the potential of employing this approach when obtaining the optimal solution is computationally demanding due to the existence of numerous alternative paths for products.

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References

  1. Diedrich, F., Jansen, K., Schwarz, U.M., Trystram, D.: A survey on approximation algorithms for scheduling with machine unavailability. In: Lerner, J., Wagner, D., Zweig, K.A. (eds.) Algorithmics of Large and Complex Networks. LNCS, vol. 5515, pp. 50–64. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02094-0_3

    Chapter  Google Scholar 

  2. Zhang, W., Judd, R.P.: Deadlock avoidance algorithm for flexible manufacturing systems by calculating effective free space of circuits. Int. J. Prod. Res. 46(13), 3441–3457 (2008)

    Article  Google Scholar 

  3. Wang, L., Hu, X., Wang, Y., Xu, S., Ma, S., Yang, K., Liu, Z., Wang, W.: Dynamic job-shop scheduling in smart manufacturing using deep reinforcement learning. Comput. Netw. 190, 107969 (2021)

    Article  Google Scholar 

  4. Du, Y., Li, J.Q., Chen, X.L., Duan, P.Y., Pan, Q.K.: Knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem’’. IEEE Trans. Emerg. Topics Comput. Intell. 7, 1036–1050 (2022)

    Article  Google Scholar 

  5. Fatemi-Anaraki, S., Tavakkoli-Moghaddam, R., Foumani, M., Vahedi-Nouri, B.: Scheduling of multi-robot job shop systems in dynamic environments: mixed-integer linear programming and constraint programming approaches. Omega 115, 102770 (2023)

    Article  Google Scholar 

  6. Zhao, Z., Liu, S., Zhou, M., Abusorrah, A.: Dual-objective mixed integer linear program and memetic algorithm for an industrial group scheduling problem. IEEE/CAA J. Automatica Sinica 8(6), 1199–1209 (2020)

    Article  Google Scholar 

  7. Wang, J., Xia, Z.: Flow-shop scheduling with a learning effect. J. Oper. Res. Soc. 56(11), 1325–1330 (2005)

    Article  Google Scholar 

  8. Boudjelida, A.: On the robustness of joint production and maintenance scheduling in presence of uncertainties. J. Intell. Manuf. 30(4), 1515–1530 (2019)

    Article  Google Scholar 

  9. Liao, W., Fu, Y.: Min-max regret criterion-based robust model for the permutation flow-shop scheduling problem. Eng. Optim. 52(4), 687–700 (2020)

    Article  MathSciNet  Google Scholar 

  10. Dong, Z., Angeli, D., De Paola, A., Strbac, G.: An iterative algorithm for regret minimization in flexible demand scheduling problems. Adv. Control Appl. Eng. Ind. Syst. 3(4), e92 (2021)

    Article  Google Scholar 

  11. Averbakh, I.: The minmax regret permutation flow-shop problem with two jobs. Eur. J. Oper. Res. 169(3), 761–766 (2006)

    Article  MathSciNet  Google Scholar 

  12. Ćwik, M., Józefczyk, J.: Evolutionary algorithm for minmax regret flow-shop problem. Manag. Prod. Eng. Rev. 6, 3–9 (2015)

    Google Scholar 

  13. Bold, M., Goerigk, M.: Investigating the recoverable robust single machine scheduling problem under interval uncertainty. Disc. Appl. Math. 313, 99–114 (2022)

    Article  MathSciNet  Google Scholar 

  14. Bozzi, A., Graffione, S., Jiménez, J., Sacile, R., Zero, E.: Reliability evaluation of emergent behaviour in a flexible manufacturing problem. In: 2023 18th Annual System of Systems Engineering Conference (SoSe), pp. 1–7 (2023)

    Google Scholar 

  15. Schulz, A.S.: Scheduling to minimize total weighted completion time: performance guarantees of LP-based heuristics and lower bounds. In: Cunningham, W.H., McCormick, S.T., Queyranne, M. (eds.) IPCO 1996. LNCS, vol. 1084, pp. 301–315. Springer, Heidelberg (1996). https://doi.org/10.1007/3-540-61310-2_23

    Chapter  Google Scholar 

  16. Trentesaux, D., et al.: Benchmarking flexible job-shop scheduling and control systems. Control. Eng. Pract. 21(9), 1204–1225 (2013)

    Article  Google Scholar 

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Correspondence to Alessandro Bozzi .

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Bozzi, A., Graffione, S., Sacile, R., Zero, E. (2024). Minimize Maximal Regret to Enhance Reliability in Flexible Open-Shop Problem. In: Borangiu, T., Trentesaux, D., Leitão, P., Berrah, L., Jimenez, JF. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2023. Studies in Computational Intelligence, vol 1136. Springer, Cham. https://doi.org/10.1007/978-3-031-53445-4_16

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