Maximizing the service level on the makespan in the stochastic flexible job-shop scheduling problem
References
[1]
Adams J., Balas E., Zawack D., The shifting bottleneck procedure for job shop scheduling, Manage. Sci. 34 (3) (1988) 391–401.
[2]
Amjad M.K., Butt S.I., Kousar R., Ahmad R., Agha M.H., Faping Z., Anjum N., Asgher U., Recent research trends in genetic algorithm based flexible job shop scheduling problems, Math. Probl. Eng. 2018 (2018).
[3]
Beck J.C., Wilson N., Proactive algorithms for job shop scheduling with probabilistic durations, J. Artificial Intelligence Res. 28 (2007) 183–232.
[4]
Birge J.R., Louveaux F., The value of information and the stochastic solution, in: Introduction to Stochastic Programming, Springer, 2011, pp. 163–177.
[5]
Brandimarte P., Routing and scheduling in a flexible job shop by tabu search, Ann. Oper. Res. 41 (3) (1993) 157–183.
[6]
Brucker P., Schlie R., Job-shop scheduling with multi-purpose machines, Computing 45 (4) (1990) 369–375.
[7]
Calafiore G., Campi M.C., Uncertain convex programs: randomized solutions and confidence levels, Math. Program. 102 (1) (2005) 25–46.
[8]
Çaliş B., Bulkan S., A research survey: review of AI solution strategies of job shop scheduling problem, J. Intell. Manuf. 26 (5) (2015) 961–973.
[9]
Campi M., Calafiore G., Decision making in an uncertain environment: the scenario-based optimization approach, Multiple Particip. Decis. Mak. (2004) 99–111.
[10]
Çatay B., Erengüç Ş.S., Vakharia A.J., Tool capacity planning in semiconductor manufacturing, Comput. Oper. Res. 30 (9) (2003) 1349–1366.
[11]
Chaudhry I.A., Khan A.A., A research survey: review of flexible job shop scheduling techniques, Int. Trans. Oper. Res. 23 (3) (2016) 551–591.
[12]
Daniels R.L., Carrillo J.E., β-Robust scheduling for single-machine systems with uncertain processing times, IIE Trans. 29 (11) (1997) 977–985.
[13]
Dauzère-Péres S., A Connected Neighborhood Structure for the Multiprocessor Job-Shop Scheduling Problem, Erasmus Universiteit/Rotterdam School of Management, Faculteit Bedrijfskunde, 1994.
[14]
Dauzère-Pérès S., Castagliola P., Lahlou C., Niveau de service en ordonnancement, in: Billaut J., Moukrim A., Sanlaville E. (Eds.), Flexibility and Robustness in Scheduling, Hermes Science Publications, 2005, pp. 97–113. (Chapter 5).
[15]
Dauzère-Pérès S., Castagliola P., Lahlou C., Service level in scheduling, in: Billaut J., Moukrim A., Sanlaville E. (Eds.), Flexibility and Robustness in Scheduling, Wiley, 2013, pp. 99–121. (Chapter 5).
[16]
Dauzère-Pérès, S., Paulli, J., 1994. Solving the General Multiprocessor Job-Shop Scheduling Problem. Management Report Series (182).
[17]
Dauzère-Pérès S., Paulli J., An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search, Ann. Oper. Res. 70 (1997) 281–306.
[18]
Flores Gómez M., Borodin V., Dauzère-Pérès S., A Monte Carlo based method to maximize the service level on the makespan in the stochastic flexible job-shop scheduling problem, in: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), IEEE, 2021, pp. 2072–2077.
[19]
Gao J., Sun L., Gen M., A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems, Comput. Oper. Res. 35 (9) (2008) 2892–2907.
[20]
García-León, A.A., Dauzère-Pérès, S., Mati, Y., 2015. Minimizing regular criteria in the Flexible Job-shop scheduling problem. In: Proceedings of the 7th Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA). pp. 443–456.
[21]
García-León A.A., Dauzère-Pérès S., Mati Y., An efficient Pareto approach for solving the multi-objective flexible job-shop scheduling problem with regular criteria, Comput. Oper. Res. 108 (2019) 187–200.
[22]
Garey M.R., Johnson D.S., Sethi R., The complexity of flowshop and jobshop scheduling, Math. Oper. Res. 1 (2) (1976) 117–129.
[23]
Gendrau M., Potvin J.-Y., Handbook of Metaheuristics, Springer, 2010, pp. 41–57. (Chapter 2).
[24]
Ghaleb M., Zolfagharinia H., Taghipour S., Real-time production scheduling in the industry-4.0 context: Addressing uncertainties in job arrivals and machine breakdowns, Comput. Oper. Res. 123 (2020).
[25]
Giles M.B., Multilevel monte carlo methods, Acta Numer. 24 (2015) 259–328.
[26]
Golenko-Ginzburg D., Kesler S., Landsman Z., Industrial job-shop scheduling with random operations and different priorities, Int. J. Prod. Econ. 40 (2–3) (1995) 185–195.
[27]
Hammersley J.M., Handscomb D.C., General principles of the monte carlo method, in: Monte Carlo Methods, Springer, 1964, pp. 50–75.
[28]
Homem-de-Mello T., Bayraksan G., Monte Carlo sampling-based methods for stochastic optimization, Surv. Oper. Res. Manag. Sci. 19 (1) (2014) 56–85.
[29]
Horng S.-C., Lin S.-S., Yang F.-Y., Evolutionary algorithm for stochastic job shop scheduling with random processing time, Expert Syst. Appl. 39 (3) (2012) 3603–3610.
[30]
Hurink J., Jurisch B., Thole M., Tabu search for the job-shop scheduling problem with multi-purpose machines, Oper.-Res.-Spektrum 15 (4) (1994) 205–215.
[31]
Jacobs J., Etman L., Van Campen E., Rooda J., Characterization of operational time variability using effective process times, IEEE Trans. Semicond. Manuf. 16 (3) (2003) 511–520.
[32]
Jamrus T., Chien C., Gen M., Sethanan K., Hybrid particle swarm optimization combined with genetic operators for flexible job-shop scheduling under uncertain processing time for semiconductor manufacturing, IEEE Trans. Semicond. Manuf. 31 (1) (2018) 32–41.
[33]
Kacem I., Hammadi S., Borne P., Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems, IEEE Trans. Syst. Man Cybern. C (Appl. Rev.) 32 (1) (2002) 1–13.
[34]
Karabuk S., Coordinating Capacity Decisions for the Supply Chain in High-Tech Industry, Lehigh University, 2001.
[35]
Knopp S., Dauzère-Pérès S., Yugma C., A batch-oblivious approach for Complex Job-Shop scheduling problems, European J. Oper. Res. 263 (1) (2017) 50–61.
[36]
Luedtke J., Ahmed S., A sample approximation approach for optimization with probabilistic constraints, SIAM J. Optim. 19 (2) (2008) 674–699.
[37]
Mahdavi I., Shirazi B., Solimanpur M., Development of a simulation-based decision support system for controlling stochastic flexible job shop manufacturing systems, Simul. Model. Pract. Theory 18 (6) (2010) 768–786.
[38]
Marshall A.W., Olkin I., Gamma and beta functions, in: Life Distributions, Springer, 2007, pp. 717–727.
[39]
Mati Y., Dauzère-Pérès S., Lahlou C., A general approach for optimizing regular criteria in the job-shop scheduling problem, European J. Oper. Res. 212 (1) (2011) 33–42.
[40]
Mokhtari H., Dadgar M., Scheduling optimization of a stochastic flexible job-shop system with time-varying machine failure rate, Comput. Oper. Res. 61 (2015) 31–45.
[41]
Mönch L., Fowler J.W., Dauzère-Pérès S., Mason S.J., Rose O., A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations, J. Sched. 14 (6) (2011) 583–599.
[42]
Mönch L., Schabacker R., Pabst D., Fowler J.W., Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops, European J. Oper. Res. 177 (3) (2007) 2100–2118.
[43]
Paulli J., A hierarchical approach for the FMS scheduling problem, European J. Oper. Res. 86 (1) (1995) 32–42.
[44]
Pezzella F., Morganti G., Ciaschetti G., A genetic algorithm for the flexible job-shop scheduling problem, Comput. Oper. Res. 35 (10) (2008) 3202–3212.
[45]
Rossi A., Dini G., Flexible job-shop scheduling with routing flexibility and separable setup times using ant colony optimisation method, Robot. Comput.-Integr. Manuf. 23 (5) (2007) 503–516.
[46]
Roy B., Sussmann B., Les problemes d’ordonnancement avec contraintes disjonctives, Note Ds 9 (1964).
[47]
Shen L., Dauzère-Pérès S., Neufeld J.S., Solving the flexible job shop scheduling problem with sequence-dependent setup times, European J. Oper. Res. 265 (2) (2018) 503–516.
[48]
Silver E.A., Pyke D.F., Peterson R., et al., Inventory Management and Production Planning and Scheduling, Vol. 3, Wiley New York, 1998.
[49]
Szántai T., Approximation of multivariate probability integrals, Encyclopedia Optim. 1 (2009) 53–59.
[50]
Tamssaouet K., Dauzère-Pérès S., Knopp S., Bitar A., Yugma C., Multiobjective optimization for complex flexible job-shop scheduling problems, European J. Oper. Res. 296 (1) (2022) 87–100.
[51]
Wu C.W., Brown K.N., Beck J.C., Scheduling with uncertain durations: Modeling β-robust scheduling with constraints, Comput. Oper. Res. 36 (8) (2009) 2348–2356.
[52]
Xing L.-N., Chen Y.-W., Yang K.-W., Multi-objective flexible job shop schedule: design and evaluation by simulation modeling, Appl. Soft Comput. 9 (1) (2009) 362–376.
[53]
Yazdani M., Amiri M., Zandieh M., Flexible job-shop scheduling with parallel variable neighborhood search algorithm, Expert Syst. Appl. 37 (1) (2010) 678–687.
[54]
Zhang R., Song S., Wu C., A two-stage hybrid particle swarm optimization algorithm for the stochastic job shop scheduling problem, Knowl.-Based Syst. 27 (2012) 393–406.
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