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On Problems and Methods of Coordinated Scheduling and Location

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Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and Perspectives (IWIFSGN 2020, BOS/SOR 2020)

Abstract

We investigate a combined approach for job scheduling on parallel machines and the location of machines referred to in the literature as ScheLoc. We sum up the up-to-date achievements and propose a general classification of such a two-part problem involving different solving methods. A sequential approach requires both parts’ successive consideration, unlike the joint proposal with their simultaneous investigation. The uncertain version is also proposed, aiming to replace the two-part deterministic problem with a single counterpart with interval release dates of jobs. The mentioned solution approaches are illustrated by specific job scheduling and machine location sub-problems.

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References

  1. Józefczyk, J., Hojda, M.: Systems approach in complex problems of decision-making and decision-support. In: Kulczycki, P., Korbicz, J., Kacprzyk, J. (eds.) Automatic Control, Robotics, and Information Processing. SSDC, vol. 296, pp. 589–615. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-48587-0_19

    Chapter  MATH  Google Scholar 

  2. Nagy, G., Salhi, S.: Location-routing: issues, models and methods. Eur. J. Oper. Res. 177, 649–672 (2007)

    Article  MathSciNet  Google Scholar 

  3. Hennes H., Hamacher H.W.: Integrated Scheduling and Location Models: Single Machine Makespan Problems. Report on Wirtschaftsmathematik, p. 82, University of Kaiserslautern (2002)

    Google Scholar 

  4. Elvikis, D., Hamacher, H.W., Kalsch M.T.: Simultaneous scheduling and location (ScheLoc): the planar ScheLoc makespan problem. J. Sched. 12(4), 361–374 (2009)

    Google Scholar 

  5. Hessler, C.J.: Scheduling-Location Algorithms with Applications in Evacuation Planning. Verlag Dr, Hut (2017)

    Google Scholar 

  6. Pinedo, M.L.: Scheduling: Theory. Algorithms. and Systems. Springer-Verlag, New York (2012). https://doi.org/10.1007/978-1-4614-2361-4

  7. Graham, R.L., Lawler, E.L., Lenstra, J.K., Rinnooy, Kan A., H.G.: Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann. Discrete Math. 5, 287–326 (1979)

    Google Scholar 

  8. Kalsch, M.T., Drezner, Z.: Solving scheduling and location problems in the plane simultaneously. Comput. Oper. Res. 37(2), 256–264 (2010)

    Article  MathSciNet  Google Scholar 

  9. Drezner, Z., Suzuki, A.: The big triangle small triangle method for the solution of nonconvex facility location problems. Oper. Res. 52(1), 128–135 (2004)

    Article  Google Scholar 

  10. Hessler, C.J., Deghdak, K.: Discrete parallel machine makespan ScheLoc problem. J. Comb. Optim. 34(4), 1159–1186 (2017)

    Article  MathSciNet  Google Scholar 

  11. Ławrynowicz, M., Józefczyk J.: A memetic algorithm for the discrete scheduling-location problem with unrelated executors. In: Proceedings of the 24th International Conference on Methods and Models in Automation and Robotics MMAR. Międzyzdroje. Poland, 26–29 August 2019

    Google Scholar 

  12. Piasecki, B.: Application of AI-based algorithms for joint problem of task scheduling and deployment of executors Master Thesis. Wroclaw University of Science and Technology. Poland (2018). (in Polish)

    Google Scholar 

  13. Piasecki, B., Józefczyk, J.: Evolutionary algorithm for joint task scheduling and deployment of executors. In: Automation of Discrete Processes. Theory and Applications Silesian University of Technology, vol. 1, pp. 169–178 (2018). (in Polish)

    Google Scholar 

  14. Rajabzadeh, M., Ziaee, M., Bozorgi-Amiri, A.: Integrated approach in solving parallel machine scheduling and location (ScheLoc) problem. Int. J. Ind. Eng. Comput. 7(4), 573–584 (2016)

    Google Scholar 

  15. Filcek, G., Józefczyk, J., Ławrynowicz, M.: An evolutionary algorithm for joint bi-criteria location-scheduling problem. Int. J. Ind. Eng. Comput. 12, 159–176 (2021)

    Google Scholar 

  16. Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester (2001)

    MATH  Google Scholar 

  17. Wesolkowski, S., Francetic, N., Grant, S.C.: Trade training device selection via multi-objective optimization. In: IEEE Congress on Evolutionary Computation (2014)

    Google Scholar 

  18. Kalai, R., Lamboray, C., Vanderpooten, D.: Lexicographic a-robustness: An alternative to min-max criteria. Euro. J. Oper. Res. 220(3), 722–728 (2020)

    Article  MathSciNet  Google Scholar 

  19. Lenstra, J.K., Rinnooy Kan, A.H.G., Brucker, P.: Complexity of machine scheduling problems. Ann. Discrete Math. 1, 343–362 (1977)

    Article  MathSciNet  Google Scholar 

  20. Garey, M.R., Johnson, D.S.: Computers and Intractability A Guide to the Theory of NP-Completeness. , W. H. Freeman and Company, New York (1979)

    MATH  Google Scholar 

  21. Downey, R.G., Fellows, M.R.: Fundamentals of Parameterized Complexity. Springer, London (2013)

    Book  Google Scholar 

  22. Liu, M., Liu, X., Zhang, E., Chu, F., Chu, Ch.: Scenario-based heuristic to two-stage stochastic program for the parallel machine ScheLoc problem. Int. J. Prod. Res. 57(6), 1706–1723 (2019)

    Article  Google Scholar 

  23. Kouvelis, P., Yu, G.: Robust Discrete Optimization and Its Applications. Kluwer Academic Publishers, London .(1997)

    Google Scholar 

  24. Rosing, K.E., Revelle, C.S., Schilling, D.A.: A gamma heuristic for the p-median problem. Eur. J. Oper. Res. 117(3), 522–532 (1999)

    Article  Google Scholar 

  25. Lin, Y.K.: Particle swarm optimization algorithm for unrelated parallel machine scheduling with release dates, Math. Probl. Eng, 2013, 409486 (2013)

    Google Scholar 

  26. Bachtler, O., Krumke, S.O., Le, H.M.: Robust single machine makespan scheduling with release date uncertainty. Oper. Res. Lett. 48, 816–819 (2020)

    Article  MathSciNet  Google Scholar 

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Correspondence to Jerzy Józefczyk .

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Józefczyk, J., Ławrynowicz, M., Filcek, G. (2022). On Problems and Methods of Coordinated Scheduling and Location. In: Atanassov, K.T., et al. Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and Perspectives. IWIFSGN BOS/SOR 2020 2020. Lecture Notes in Networks and Systems, vol 338. Springer, Cham. https://doi.org/10.1007/978-3-030-95929-6_12

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