{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T14:33:44Z","timestamp":1772807624102,"version":"3.50.1"},"reference-count":97,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Pontifical Xavierian University"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann Oper Res"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper addresses a stochastic job shop scheduling problem with sequence-dependent setup times, aiming to minimize the expected maximum lateness. The stochastic nature is modeled by considering uncertain times between failures (TBF) and uncertain times to repair (TTR). To tackle this problem, a simheuristic approach is proposed, which combines a tabu search (TS) algorithm with Monte Carlo simulation. A total of 320 instances were used to conduct multiple experiments. Instances were generated with two distributions to study the behavior of stochastic TTR and TBF under log-normal and exponential distributions. Firstly, the performance of the simheuristic was evaluated for small instances by comparing it with the simulation of optimal solutions obtained with a mixed-integer linear programming (MILP) model. The simheuristic approach demonstrated an average improvement of around 7% compared to the simulation of MILP model solutions. Secondly, the simheuristic performance was evaluated for medium and large-size instances by comparing it with the simulation of the solutions obtained by the earliest due date (EDD) and process time plus work in the next queue plus negative slack (PT\u2009+\u2009WINQ\u2009+\u2009SL) dispatching rules. The results showed an average improvement of around 11% compared to EDD and 14% compared to PT\u2009+\u2009WINQ\u2009+\u2009SL. Furthermore, the results highlight that even when the two distributions have the same expected value and coefficient of variation, they can yield different expected maximum lateness values. This emphasizes the importance of precise distribution fitting when solving real cases to achieve effective scheduling performance.<\/jats:p>","DOI":"10.1007\/s10479-023-05592-z","type":"journal-article","created":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T05:01:22Z","timestamp":1696222882000},"page":"801-833","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Minimizing the expected maximum lateness for a job shop subject to stochastic machine breakdowns"],"prefix":"10.1007","volume":"338","author":[{"given":"Gabriel Mauricio","family":"Zambrano-Rey","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4590-3401","authenticated-orcid":false,"given":"Eliana Mar\u00eda","family":"Gonz\u00e1lez-Neira","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel Fernando","family":"Forero-Ortiz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda Jos\u00e9","family":"Ocampo-Monsalve","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrea","family":"Rivera-Torres","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,2]]},"reference":[{"key":"5592_CR1","first-page":"4","volume":"11","author":"M Abdolrazzagh","year":"2017","unstructured":"Abdolrazzagh, M., & Adbullah, S. (2017). Job Shop scheduling: classification, constraints and objective funtions. World Academy of Science-Engineering and Technology, 11, 4\u201320.","journal-title":"World Academy of Science-Engineering and Technology"},{"issue":"5","key":"5592_CR2","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1080\/15325000252888425","volume":"30","author":"MA Abido","year":"2002","unstructured":"Abido, M. A. (2002). Optimal power flow using tabu search algorithm. Electric Power Components and Systems, 30(5), 469\u2013483. https:\/\/doi.org\/10.1080\/15325000252888425","journal-title":"Electric Power Components and Systems"},{"issue":"3","key":"5592_CR3","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1287\/mnsc.34.3.391","volume":"34","author":"J Adams","year":"1988","unstructured":"Adams, J., Balas, E., & Zawack, D. (1988). The shifting bottleneck procedure for job shop scheduling. Management Science, 34(3), 391\u2013401.","journal-title":"Management Science"},{"issue":"1","key":"5592_CR4","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/J.ESWA.2009.05.001","volume":"37","author":"MA Adibi","year":"2010","unstructured":"Adibi, M. A., Zandieh, M., & Amiri, M. (2010). Multi-objective scheduling of dynamic job shop using variable neighborhood search. Expert Systems with Applications, 37(1), 282\u2013287. https:\/\/doi.org\/10.1016\/J.ESWA.2009.05.001","journal-title":"Expert Systems with Applications"},{"issue":"4","key":"5592_CR5","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1287\/opre.3.4.429","volume":"3","author":"SB Akers","year":"1955","unstructured":"Akers, S. B., & Friedman, J. (1955). A Non-numerical approach to production scheduling problems. Journal of the Operations Research Society of America, 3(4), 429\u2013442. https:\/\/doi.org\/10.1287\/opre.3.4.429","journal-title":"Journal of the Operations Research Society of America"},{"issue":"2","key":"5592_CR6","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/J.IJPE.2011.04.020","volume":"132","author":"N Al-Hinai","year":"2011","unstructured":"Al-Hinai, N., & Elmekkawy, T. Y. (2011). Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm. International Journal of Production Economics, 132(2), 279\u2013291. https:\/\/doi.org\/10.1016\/J.IJPE.2011.04.020","journal-title":"International Journal of Production Economics"},{"issue":"3","key":"5592_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1299\/jamdsm.2016jamdsm0053","volume":"10","author":"K Araki","year":"2016","unstructured":"Araki, K., & Yoshitomi, Y. (2016). Stochastic job-shop scheduling: A hybrid approach combining pseudo particle swarm optimization and the Monte Carlo method. Journal of Advanced Mechanical Design, Systems and Manufacturing, 10(3), 1\u201310. https:\/\/doi.org\/10.1299\/jamdsm.2016jamdsm0053","journal-title":"Journal of Advanced Mechanical Design, Systems and Manufacturing"},{"key":"5592_CR8","doi-asserted-by":"publisher","first-page":"113879","DOI":"10.1016\/j.eswa.2020.113879","volume":"162","author":"A Aschauer","year":"2020","unstructured":"Aschauer, A., Roetzer, F., Steinboeck, A., & Kugi, A. (2020a). Efficient scheduling of a stochastic no-wait job shop with controllable processing times. Expert Systems with Applications, 162, 113879. https:\/\/doi.org\/10.1016\/j.eswa.2020.113879","journal-title":"Expert Systems with Applications"},{"issue":"2","key":"5592_CR9","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1080\/00207543.2010.539281","volume":"50","author":"A Azadeh","year":"2012","unstructured":"Azadeh, A., Negahban, A., & Moghaddam, M. (2012). A hybrid computer simulation-artificial neural network algorithm for optimisation of dispatching rule selection in stochastic job shop scheduling problems. International Journal of Production Research, 50(2), 551\u2013566. https:\/\/doi.org\/10.1080\/00207543.2010.539281","journal-title":"International Journal of Production Research"},{"issue":"3","key":"5592_CR10","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1287\/opre.13.3.358","volume":"13","author":"BP Banerjee","year":"1965","unstructured":"Banerjee, B. P. (1965). Single facility sequencing with random execution times. Operations Research, 13(3), 358\u2013364. https:\/\/doi.org\/10.1287\/opre.13.3.358","journal-title":"Operations Research"},{"issue":"17","key":"5592_CR11","doi-asserted-by":"publisher","first-page":"4523","DOI":"10.1080\/00207540210147043","volume":"40","author":"A Baykasoglu","year":"2002","unstructured":"Baykasoglu, A. (2002). Linguistic-based meta-heuristic optimization model for flexible job shop scheduling. International Journal of Production Research, 40(17), 4523\u20134543. https:\/\/doi.org\/10.1080\/00207540210147043","journal-title":"International Journal of Production Research"},{"key":"5592_CR12","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1613\/jair.2080","volume":"28","author":"JC Beck","year":"2007","unstructured":"Beck, J. C., & Wilson, N. (2007). Proactive algorithms for job shop scheduling with probabilistic durations. Journal of Artificial Intelligence Research, 28, 183\u2013232. https:\/\/doi.org\/10.1613\/jair.2080","journal-title":"Journal of Artificial Intelligence Research"},{"issue":"3","key":"5592_CR13","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1016\/j.ejor.2017.03.030","volume":"261","author":"C Bierwirth","year":"2017","unstructured":"Bierwirth, C., & Kuhpfahl, J. (2017). Extended GRASP for the job shop scheduling problem with total weighted tardiness objective. European Journal of Operational Research, 261(3), 835\u2013848. https:\/\/doi.org\/10.1016\/j.ejor.2017.03.030","journal-title":"European Journal of Operational Research"},{"issue":"7\u20138","key":"5592_CR14","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1007\/S00170-003-1771-2\/FIGURES\/11","volume":"23","author":"O Bilkay","year":"2004","unstructured":"Bilkay, O., Anlagan, O., & Kilic, S. E. (2004). Job shop scheduling using fuzzy logic. International Journal of Advanced Manufacturing Technology, 23(7\u20138), 606\u2013619. https:\/\/doi.org\/10.1007\/S00170-003-1771-2\/FIGURES\/11","journal-title":"International Journal of Advanced Manufacturing Technology"},{"issue":"7","key":"5592_CR15","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.1002\/NAV.20036","volume":"51","author":"R Bollapragada","year":"2004","unstructured":"Bollapragada, R., & Sadeh, N. M. (2004). Proactive release procedures for just-in-time job shop environments, subject to machine failures. Naval Research Logistics (NRL), 51(7), 1018\u20131044. https:\/\/doi.org\/10.1002\/NAV.20036","journal-title":"Naval Research Logistics (NRL)"},{"issue":"1\u20133","key":"5592_CR16","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/S0925-5273(99)00048-1","volume":"64","author":"V Botta-Genoulaz","year":"2000","unstructured":"Botta-Genoulaz, V. (2000). Hybrid flow shop scheduling with precedence constraints and time lags to minimize maximum lateness. International Journal of Production Economics, 64(1\u20133), 101\u2013111. https:\/\/doi.org\/10.1016\/S0925-5273(99)00048-1","journal-title":"International Journal of Production Economics"},{"issue":"440","key":"5592_CR17","doi-asserted-by":"publisher","first-page":"1494","DOI":"10.1080\/01621459.1997.10473671","volume":"92","author":"E Brunner","year":"1997","unstructured":"Brunner, E., Dette, H., & Munk, A. (1997). Box-type approximations in nonparametric factorial designs. Journal of the American Statistical Association, 92(440), 1494\u20131502. https:\/\/doi.org\/10.1080\/01621459.1997.10473671","journal-title":"Journal of the American Statistical Association"},{"issue":"5","key":"5592_CR18","doi-asserted-by":"publisher","first-page":"961","DOI":"10.1007\/s10845-013-0837-8","volume":"26","author":"B \u00c7ali\u015f","year":"2015","unstructured":"\u00c7ali\u015f, B., & Bulkan, S. (2015). A research survey: Review of AI solution strategies of job shop scheduling problem. Journal of Intelligent Manufacturing, 26(5), 961\u2013973. https:\/\/doi.org\/10.1007\/s10845-013-0837-8","journal-title":"Journal of Intelligent Manufacturing"},{"key":"5592_CR19","doi-asserted-by":"publisher","first-page":"3556","DOI":"10.1109\/CDC.1997.652402","volume":"4","author":"D Chen","year":"1997","unstructured":"Chen, D., Liu, F., & Luh, P. B. (1997). Scheduling job shops with uncertainties. Proceedings of the IEEE Conference on Decision and Control, 4, 3556\u20133561. https:\/\/doi.org\/10.1109\/CDC.1997.652402","journal-title":"Proceedings of the IEEE Conference on Decision and Control"},{"issue":"7","key":"5592_CR20","doi-asserted-by":"publisher","first-page":"573","DOI":"10.3390\/machines10070573","volume":"10","author":"S Chen","year":"2022","unstructured":"Chen, S., Huang, Z., & Guo, H. (2022). An end-to-end deep learning method for dynamic job shop scheduling problem. Machines, 10(7), 573. https:\/\/doi.org\/10.3390\/machines10070573","journal-title":"Machines"},{"key":"5592_CR21","doi-asserted-by":"publisher","unstructured":"Cheng, M., Sugi, M., Ota, J., Yamamoto, M., Ito, H., & Inoue, K. (2005). Online job shop rescheduling with reaction-diffusion equation on a graph. In 2005 IEEE\/RSJ International Conference on Intelligent Robots and Systems, IROS, 3219\u20133224. https:\/\/doi.org\/10.1109\/IROS.2005.1545459","DOI":"10.1109\/IROS.2005.1545459"},{"issue":"2","key":"5592_CR22","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/s10479-013-1332-5","volume":"242","author":"TCE Cheng","year":"2016","unstructured":"Cheng, T. C. E., Peng, B., & L\u00fc, Z. (2016). A hybrid evolutionary algorithm to solve the job shop scheduling problem. Annals of Operations Research, 242(2), 223\u2013237. https:\/\/doi.org\/10.1007\/s10479-013-1332-5","journal-title":"Annals of Operations Research"},{"issue":"3\/4","key":"5592_CR23","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1504\/IJMTM.2016.077813","volume":"30","author":"PH Chiang","year":"2016","unstructured":"Chiang, P. H., & Torng, C. C. (2016). A production planning and optimisation of multi-mode job shop scheduling problem for an avionics manufacturing plant. International Journal of Manufacturing Technology and Management, 30(3\/4), 179. https:\/\/doi.org\/10.1504\/IJMTM.2016.077813","journal-title":"International Journal of Manufacturing Technology and Management"},{"issue":"10","key":"5592_CR24","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1057\/s41274-016-0155-6","volume":"68","author":"J de Armas","year":"2017","unstructured":"de Armas, J., Juan, A. A., Marqu\u00e8s, J. M., & Pedroso, J. P. (2017). Solving the deterministic and stochastic uncapacitated facility location problem: From a heuristic to a simheuristic. Journal of the Operational Research Society, 68(10), 1161\u20131176. https:\/\/doi.org\/10.1057\/s41274-016-0155-6","journal-title":"Journal of the Operational Research Society"},{"issue":"3","key":"5592_CR25","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/BF01305874","volume":"13","author":"J Fang","year":"1997","unstructured":"Fang, J., & Xi, Y. (1997). A rolling horizon job shop rescheduling strategy in the dynamic environment. The International Journal of Advanced Manufacturing Technology, 13(3), 227\u2013232. https:\/\/doi.org\/10.1007\/BF01305874","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"5592_CR26","doi-asserted-by":"publisher","unstructured":"Feng, X., Zhao, Z., & Zhang, C. (2020). Simulation optimization framework for online deployment and adjustment of reconfigurable machines in job shops. In IEEE International Conference on Industrial Engineering and Engineering Management, 2020-Decem, 731\u2013735. https:\/\/doi.org\/10.1109\/IEEM45057.2020.9309782","DOI":"10.1109\/IEEM45057.2020.9309782"},{"issue":"2","key":"5592_CR27","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/BF01096763","volume":"6","author":"TA Feo","year":"1995","unstructured":"Feo, T. A., & Resende, M. G. C. (1995). Greedy randomized adaptive search procedures. Journal of Global Optimization, 6(2), 109\u2013133. https:\/\/doi.org\/10.1007\/BF01096763","journal-title":"Journal of Global Optimization"},{"issue":"3","key":"5592_CR28","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1016\/j.ejor.2016.09.055","volume":"257","author":"V Fernandez-Viagas","year":"2017","unstructured":"Fernandez-Viagas, V., Ruiz, R., & Framinan, J. M. (2017). A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation. European Journal of Operational Research, 257(3), 707\u2013721. https:\/\/doi.org\/10.1016\/j.ejor.2016.09.055","journal-title":"European Journal of Operational Research"},{"key":"5592_CR30","doi-asserted-by":"publisher","unstructured":"Fisher, M. L. (1973). optimal solution of scheduling problems using lagrange multipliers: Part II. In Symposium on the Theory of Scheduling and its Applications. https:\/\/doi.org\/10.1007\/978-3-642-80784-8_20","DOI":"10.1007\/978-3-642-80784-8_20"},{"key":"5592_CR29","unstructured":"Fisher, H., & Thompson, G. L. (1963). Probabilistic learning combinations of local job-shop scheduling rules. In J. F. Muth & G. L. Thompson (Ed.), Industrial Scheduling (pp. 225\u2013251). Prentice-Hall."},{"key":"5592_CR31","volume-title":"Organizing for work","author":"HL Gantt","year":"1919","unstructured":"Gantt, H. L. (1919). Organizing for work. Harcourt."},{"key":"5592_CR32","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/s00170-008-1577-3","volume":"42","author":"M Gholami","year":"2009","unstructured":"Gholami, M., Zandieh, M., & Alem-Tabriz, A. (2009). Scheduling hybrid flow shop with sequence-dependent setup times and machines with random breakdowns. The International Journal of Advanced Manufacturing Technology, 42, 189\u2013201.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"5592_CR33","doi-asserted-by":"publisher","unstructured":"Giacaman, G. J., Medel, R. P., & Tabilo, J. A. (2002). Simulation of the material transporting and loading process in Pedro de Valdivia mine. In Proceedings of the Winter Simulation Conference, pp. 1349\u20131355. https:\/\/doi.org\/10.1109\/WSC.2002.1166401","DOI":"10.1109\/WSC.2002.1166401"},{"key":"5592_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2020.01.039","author":"J Gmys","year":"2020","unstructured":"Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem. European Journal of Operational Research. https:\/\/doi.org\/10.1016\/j.ejor.2020.01.039","journal-title":"European Journal of Operational Research"},{"key":"5592_CR35","doi-asserted-by":"publisher","DOI":"10.1057\/jos.2016.11","author":"S Gonz\u00e1lez-Mart\u00edn","year":"2016","unstructured":"Gonz\u00e1lez-Mart\u00edn, S., Juan, A., Riera, D., Elizondo, M., & Ramos-Gonz\u00e1lez, J. (2016). A Simheuristic algorithm for solving the arc routing problem with stochastic demands. Journal of Simulation. https:\/\/doi.org\/10.1057\/jos.2016.11","journal-title":"Journal of Simulation"},{"key":"5592_CR36","doi-asserted-by":"publisher","first-page":"57","DOI":"10.5267\/j.jpm.2019.1.003","volume":"4","author":"EM Gonz\u00e1lez-Neira","year":"2019","unstructured":"Gonz\u00e1lez-Neira, E. M., & Montoya-Torres, J. R. (2019). A simheuristic for bi-objective stochastic permutation flow shop scheduling problem. Journal of Project Management, 4, 57\u201380. https:\/\/doi.org\/10.5267\/j.jpm.2019.1.003","journal-title":"Journal of Project Management"},{"key":"5592_CR37","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.cie.2018.06.036","volume":"123","author":"A Gruler","year":"2018","unstructured":"Gruler, A., Panadero, J., de Armas, J., Moreno P\u00e9rez, J. A., & Juan, A. A. (2018). Combining variable neighborhood search with simulation for the inventory routing problem with stochastic demands and stock-outs. Computers & Industrial Engineering, 123, 278\u2013288. https:\/\/doi.org\/10.1016\/j.cie.2018.06.036","journal-title":"Computers & Industrial Engineering"},{"issue":"3","key":"5592_CR38","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1007\/s10845-014-1026-0","volume":"28","author":"X Hao","year":"2017","unstructured":"Hao, X., Gen, M., Lin, L., & Suer, G. A. (2017). Effective multiobjective EDA for bi-criteria stochastic job-shop scheduling problem. Journal of Intelligent Manufacturing, 28(3), 833\u2013845. https:\/\/doi.org\/10.1007\/s10845-014-1026-0","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"2","key":"5592_CR39","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/S10696-011-9094-3\/FIGURES\/5","volume":"23","author":"SMK Hasan","year":"2011","unstructured":"Hasan, S. M. K., Sarker, R., Essam, D., & Kacem, I. (2011). A DSS for job scheduling under process interruptions. Flexible Services and Manufacturing Journal, 23(2), 137\u2013155. https:\/\/doi.org\/10.1007\/S10696-011-9094-3\/FIGURES\/5","journal-title":"Flexible Services and Manufacturing Journal"},{"key":"5592_CR40","doi-asserted-by":"publisher","unstructured":"Hill, C. (2011). Negocios Internacionales. In Corporate environmental orientation: Conceptualization and the case of Andean exporters (Vol. 30). https:\/\/doi.org\/10.1039\/C4NJ00351A","DOI":"10.1039\/C4NJ00351A"},{"issue":"1","key":"5592_CR41","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/S0360-8352(99)00006-6","volume":"36","author":"O Holthaus","year":"1999","unstructured":"Holthaus, O. (1999). Scheduling in job shops with machine breakdowns: An experimental study. Computers & Industrial Engineering, 36(1), 137\u2013162. https:\/\/doi.org\/10.1016\/S0360-8352(99)00006-6","journal-title":"Computers & Industrial Engineering"},{"issue":"3","key":"5592_CR42","doi-asserted-by":"publisher","first-page":"3603","DOI":"10.1016\/j.eswa.2011.09.050","volume":"39","author":"S-C Horng","year":"2012","unstructured":"Horng, S.-C., Lin, S.-S., & Yang, F.-Y. (2012). Evolutionary algorithm for stochastic job shop scheduling with random processing time. Expert Systems with Applications, 39(3), 3603\u20133610. https:\/\/doi.org\/10.1016\/j.eswa.2011.09.050","journal-title":"Expert Systems with Applications"},{"issue":"3","key":"5592_CR43","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1002\/nav.3800030307","volume":"3","author":"JR Jackson","year":"1956","unstructured":"Jackson, J. R. (1956). An extension of Johnson\u2019s results on job IDT scheduling. Naval Research Logistics Quarterly, 3(3), 201\u2013203. https:\/\/doi.org\/10.1002\/nav.3800030307","journal-title":"Naval Research Logistics Quarterly"},{"issue":"4","key":"5592_CR44","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1108\/02635579410059455","volume":"94","author":"LW Jacobs","year":"1994","unstructured":"Jacobs, L. W., & Lauer, J. (1994). DSS for job shop machine scheduling. Industrial Management & Data Systems, 94(4), 15\u201323. https:\/\/doi.org\/10.1108\/02635579410059455","journal-title":"Industrial Management & Data Systems"},{"issue":"2","key":"5592_CR45","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1016\/S0377-2217(98)00113-1","volume":"113","author":"AS Jain","year":"1999","unstructured":"Jain, A. S., & Meeran, S. (1999). Deterministic job-shop scheduling: Past, present and future. European Journal of Operational Research, 113(2), 390\u2013434. https:\/\/doi.org\/10.1016\/S0377-2217(98)00113-1","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"5592_CR46","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1002\/nav.3800010110","volume":"1","author":"SM Johnson","year":"1954","unstructured":"Johnson, S. M. (1954). Optimal two- and three-stage production schedules with setup times included. Naval Research Logistics Quarterly, 1(1), 61\u201368. https:\/\/doi.org\/10.1002\/nav.3800010110","journal-title":"Naval Research Logistics Quarterly"},{"key":"5592_CR47","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.simpat.2014.02.005","volume":"46","author":"AA Juan","year":"2014","unstructured":"Juan, A. A., Barrios, B. B., Vallada, E., Riera, D., & Jorba, J. (2014). A simheuristic algorithm for solving the permutation flow shop problem with stochastic processing times. Simulation Modelling Practice and Theory, 46, 101\u2013117. https:\/\/doi.org\/10.1016\/j.simpat.2014.02.005","journal-title":"Simulation Modelling Practice and Theory"},{"key":"5592_CR48","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.orp.2015.03.001","volume":"2","author":"AA Juan","year":"2015","unstructured":"Juan, A. A., Faulin, J., Grasman, S. E., Rabe, M., & Figueira, G. (2015). A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspectives, 2, 62\u201372. https:\/\/doi.org\/10.1016\/j.orp.2015.03.001","journal-title":"Operations Research Perspectives"},{"issue":"3","key":"5592_CR49","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1108\/02635579910370652","volume":"99","author":"SN Kadipasaoglu","year":"1999","unstructured":"Kadipasaoglu, S. N., Peixoto, J. L., & Khumawala, B. M. (1999). Global manufacturing practices: An empirical evaluation. Industrial Management & Data Systems, 99(3), 101\u2013108. https:\/\/doi.org\/10.1108\/02635579910370652","journal-title":"Industrial Management & Data Systems"},{"key":"5592_CR50","unstructured":"Lawrence, S. (1984). Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques (Supplement). Carnegie Mellon University, Pittsburgh, PA: Graduate School of Industrial Administration."},{"issue":"8","key":"5592_CR51","doi-asserted-by":"publisher","first-page":"4991","DOI":"10.1016\/J.ASOC.2011.06.001","volume":"11","author":"D Lei","year":"2011","unstructured":"Lei, D. (2011). Simplified multi-objective genetic algorithms for stochastic job shop scheduling. Applied Soft Computing, 11(8), 4991\u20134996. https:\/\/doi.org\/10.1016\/J.ASOC.2011.06.001","journal-title":"Applied Soft Computing"},{"issue":"24","key":"5592_CR52","doi-asserted-by":"publisher","first-page":"11851","DOI":"10.1016\/J.AMC.2012.04.091","volume":"218","author":"DM Lei","year":"2012","unstructured":"Lei, D. M. (2012). Minimizing makespan for scheduling stochastic job shop with random breakdown. Applied Mathematics and Computation, 218(24), 11851\u201311858. https:\/\/doi.org\/10.1016\/J.AMC.2012.04.091","journal-title":"Applied Mathematics and Computation"},{"key":"5592_CR53","doi-asserted-by":"publisher","unstructured":"Li, Y., & Chen, Y. (2009). Neural network and genetic algorithm-based hybrid approach to dynamic job shop scheduling problem. In Conference Proceedings-IEEE International Conference on Systems, Man and Cybernetics, 4836\u20134841. https:\/\/doi.org\/10.1109\/ICSMC.2009.5346060","DOI":"10.1109\/ICSMC.2009.5346060"},{"key":"5592_CR54","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1016\/j.jclepro.2018.02.004","volume":"181","author":"JQ Li","year":"2018","unstructured":"Li, J. Q., Sang, H. Y., Han, Y. Y., Wang, C. G., & Gao, K. Z. (2018). Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions. Journal of Cleaner Production, 181, 584\u2013598. https:\/\/doi.org\/10.1016\/j.jclepro.2018.02.004","journal-title":"Journal of Cleaner Production"},{"key":"5592_CR55","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/978-3-662-55305-3_17\/TABLES\/12","volume":"2","author":"X Li","year":"2020","unstructured":"Li, X., & Gao, L. (2020). A hybrid intelligent algorithm and rescheduling technique for dynamic JSP. Engineering Applications of Computational Methods, 2, 345\u2013375. https:\/\/doi.org\/10.1007\/978-3-662-55305-3_17\/TABLES\/12","journal-title":"Engineering Applications of Computational Methods"},{"key":"5592_CR56","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1109\/SSST.2004.1295656","volume":"36","author":"N Liu","year":"2004","unstructured":"Liu, N., Abdelrahman, M. A., & Ramaswamy, S. (2004). A multi-agent model for reactive job shop scheduling. Proceedings of the Annual Southeastern Symposium on System Theory, 36, 241\u2013245. https:\/\/doi.org\/10.1109\/SSST.2004.1295656","journal-title":"Proceedings of the Annual Southeastern Symposium on System Theory"},{"key":"5592_CR57","first-page":"32","volume":"8","author":"T Makino","year":"1965","unstructured":"Makino, T. (1965). On a scheduling problem. Journal of the Operations Research Society Japan, 8, 32\u201344.","journal-title":"Journal of the Operations Research Society Japan"},{"key":"5592_CR58","doi-asserted-by":"publisher","DOI":"10.1287\/opre.8.2.219","author":"AS Manne","year":"1960","unstructured":"Manne, A. S. (1960). On the job-shop scheduling problem. Operations Research. https:\/\/doi.org\/10.1287\/opre.8.2.219","journal-title":"Operations Research"},{"issue":"1","key":"5592_CR59","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1023\/B:ANOR.0000039520.24932.4b","volume":"131","author":"C Meloni","year":"2004","unstructured":"Meloni, C., Pacciarelli, D., & Pranzo, M. (2004). A rollout metaheuristic for job shop scheduling problems. Annals of Operations Research, 131(1), 215\u2013235. https:\/\/doi.org\/10.1023\/B:ANOR.0000039520.24932.4b","journal-title":"Annals of Operations Research"},{"key":"5592_CR60","doi-asserted-by":"publisher","first-page":"106347","DOI":"10.1016\/j.cie.2020.106347","volume":"142","author":"L Meng","year":"2020","unstructured":"Meng, L., Zhang, C., Ren, Y., Zhang, B., & Lv, C. (2020). Mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem. Computers & Industrial Engineering, 142, 106347. https:\/\/doi.org\/10.1016\/j.cie.2020.106347","journal-title":"Computers & Industrial Engineering"},{"issue":"7","key":"5592_CR61","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1080\/08839510600779738","volume":"20","author":"P Mizrak","year":"2006","unstructured":"Mizrak, P., & Bayhan, G. M. (2006). Comparative study of dispatching rules in a real-life job shop environment. Applied Artificial Intelligence, 20(7), 585\u2013607. https:\/\/doi.org\/10.1080\/08839510600779738","journal-title":"Applied Artificial Intelligence"},{"key":"5592_CR62","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.promfg.2019.02.006","volume":"30","author":"J Mohan","year":"2019","unstructured":"Mohan, J., Lanka, K., & Rao, A. N. (2019). A review of dynamic job shop scheduling techniques. Procedia Manufacturing, 30, 34\u201339. https:\/\/doi.org\/10.1016\/j.promfg.2019.02.006","journal-title":"Procedia Manufacturing"},{"issue":"2","key":"5592_CR63","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1080\/00207548208947763","volume":"20","author":"AP Muhlemann","year":"1982","unstructured":"Muhlemann, A. P., Lockett, A. G., & Farn, C. K. (1982). Job shop scheduling heuristics and frequency of scheduling. International Journal of Production Research, 20(2), 227\u2013241. https:\/\/doi.org\/10.1080\/00207548208947763","journal-title":"International Journal of Production Research"},{"issue":"2","key":"5592_CR64","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.knosys.2009.06.002","volume":"23","author":"B Naderi","year":"2010","unstructured":"Naderi, B., Tavakkoli-Moghaddam, R., & Khalili, M. (2010). Electromagnetism-like mechanism and simulated annealing algorithms for flowshop scheduling problems minimizing the total weighted tardiness and makespan. Knowledge-Based Systems, 23(2), 77\u201385. https:\/\/doi.org\/10.1016\/j.knosys.2009.06.002","journal-title":"Knowledge-Based Systems"},{"issue":"2","key":"5592_CR65","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/s10951-005-6364-5","volume":"8","author":"E Nowicki","year":"2005","unstructured":"Nowicki, E., & Smutnicki, C. (2005). An advanced tabu search algorithm for the job shop problem. Journal of Scheduling, 8(2), 145\u2013159. https:\/\/doi.org\/10.1007\/s10951-005-6364-5","journal-title":"Journal of Scheduling"},{"issue":"1","key":"5592_CR66","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1080\/12460125.1992.10511509","volume":"1","author":"J Paredis","year":"1992","unstructured":"Paredis, J., & Van Rij, T. (1992). Simulation and constraint programming as support methodologies for job shop scheduling. Journal of Decision Systems, 1(1), 59\u201377. https:\/\/doi.org\/10.1080\/12460125.1992.10511509","journal-title":"Journal of Decision Systems"},{"issue":"1","key":"5592_CR67","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1007\/s10479-007-0287-9","volume":"159","author":"S Petrovic","year":"2008","unstructured":"Petrovic, S., Fayad, C., Petrovic, D., Burke, E., & Kendall, G. (2008). Fuzzy job shop scheduling with lot-sizing. Annals of Operations Research, 159(1), 275\u2013292. https:\/\/doi.org\/10.1007\/s10479-007-0287-9","journal-title":"Annals of Operations Research"},{"key":"5592_CR68","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-26580-3","volume-title":"Scheduling","author":"ML Pinedo","year":"2016","unstructured":"Pinedo, M. L. (2016). Scheduling (5th ed.). Springer International Publishing.","edition":"5"},{"issue":"4","key":"5592_CR69","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1007\/s10732-014-9279-5","volume":"22","author":"M Pranzo","year":"2016","unstructured":"Pranzo, M., & Pacciarelli, D. (2016). An iterated greedy metaheuristic for the blocking job shop scheduling problem. Journal of Heuristics, 22(4), 587\u2013611. https:\/\/doi.org\/10.1007\/s10732-014-9279-5","journal-title":"Journal of Heuristics"},{"key":"5592_CR70","doi-asserted-by":"publisher","DOI":"10.1080\/17477778.2019.1680262","author":"CL Quintero-Araujo","year":"2019","unstructured":"Quintero-Araujo, C. L., Guimarans, D., & Juan, A. A. (2019). A simheuristic algorithm for the capacitated location routing problem with stochastic demands. Journal of Simulation. https:\/\/doi.org\/10.1080\/17477778.2019.1680262","journal-title":"Journal of Simulation"},{"key":"5592_CR71","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-60566-798-0.CH012","author":"P Renna","year":"2009","unstructured":"Renna, P. (2009). A performance comparison between efficiency and pheromone approaches in dynamic manufacturing scheduling. Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications. https:\/\/doi.org\/10.4018\/978-1-60566-798-0.CH012","journal-title":"Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications"},{"key":"5592_CR72","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-013-5131-6","author":"S Roshan","year":"2013","unstructured":"Roshan, S., Jooibari, M., Teimouri, R., Asgharzadeh-Ahmadi, G., Falahati-Naghibi, M., & Sohrabpoor, H. (2013). Optimization of friction stir welding process of AA7075 aluminum alloy to achieve desirable mechanical properties using ANFIS models and simulated annealing algorithm. The International Journal of Advanced Manufacturing Technology. https:\/\/doi.org\/10.1007\/s00170-013-5131-6","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"issue":"4","key":"5592_CR73","doi-asserted-by":"publisher","first-page":"665","DOI":"10.5505\/pajes.2017.47108","volume":"24","author":"\u00c7 Sel","year":"2018","unstructured":"Sel, \u00c7., & Hamzaday\u0131, A. (2018). A simulated annealing approach based simulation-optimisation to the dynamic job-shop scheduling problem. Pamukkale University Journal of Engineering Sciences, 24(4), 665\u2013674. https:\/\/doi.org\/10.5505\/pajes.2017.47108","journal-title":"Pamukkale University Journal of Engineering Sciences"},{"key":"5592_CR74","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.procir.2021.11.069","volume":"104","author":"S Shady","year":"2021","unstructured":"Shady, S., Kaihara, T., Fujii, N., & Kokuryo, D. (2021). Evolving dispatching rules using genetic programming for multi-objective dynamic job shop scheduling with machine breakdowns. Procedia CIRP, 104, 411\u2013416. https:\/\/doi.org\/10.1016\/j.procir.2021.11.069","journal-title":"Procedia CIRP"},{"key":"5592_CR75","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.cie.2017.05.026","volume":"110","author":"J Shahrabi","year":"2017","unstructured":"Shahrabi, J., Adibi, M. A., & Mahootchi, M. (2017). A reinforcement learning approach to parameter estimation in dynamic job shop scheduling. Computers & Industrial Engineering, 110, 75\u201382.","journal-title":"Computers & Industrial Engineering"},{"issue":"4","key":"5592_CR76","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1016\/J.JMSY.2013.04.015","volume":"32","author":"N Shahsavari-Pour","year":"2013","unstructured":"Shahsavari-Pour, N., & Ghasemishabankareh, B. (2013). A novel hybrid meta-heuristic algorithm for solving multi objective flexible job shop scheduling. Journal of Manufacturing Systems, 32(4), 771\u2013780. https:\/\/doi.org\/10.1016\/J.JMSY.2013.04.015","journal-title":"Journal of Manufacturing Systems"},{"issue":"1\u20132","key":"5592_CR77","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1002\/nav.3800030106","volume":"3","author":"WE Smith","year":"1956","unstructured":"Smith, W. E. (1956). Various optimizers for single-stage production. Naval Research Logistics Quarterly, 3(1\u20132), 59\u201366. https:\/\/doi.org\/10.1002\/nav.3800030106","journal-title":"Naval Research Logistics Quarterly"},{"issue":"9\u201310","key":"5592_CR78","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1007\/S00170-003-1601-6\/FIGURES\/8","volume":"22","author":"V Subramaniam","year":"2003","unstructured":"Subramaniam, V., & Raheja, A. S. (2003). mAOR: A heuristic-based reactive repair mechanism for job shop schedules. International Journal of Advanced Manufacturing Technology, 22(9\u201310), 669\u2013680. https:\/\/doi.org\/10.1007\/S00170-003-1601-6\/FIGURES\/8","journal-title":"International Journal of Advanced Manufacturing Technology"},{"issue":"1","key":"5592_CR79","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/J.CIE.2007.04.002","volume":"53","author":"H Suwa","year":"2007","unstructured":"Suwa, H., & Sandoh, H. (2007). Capability of cumulative delay based reactive scheduling for job shops with machine breakdowns. Computers & Industrial Engineering, 53(1), 63\u201378. https:\/\/doi.org\/10.1016\/J.CIE.2007.04.002","journal-title":"Computers & Industrial Engineering"},{"key":"5592_CR80","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cie.2018.08.008","volume":"125","author":"K Tamssaouet","year":"2018","unstructured":"Tamssaouet, K., Dauz\u00e8re-P\u00e9r\u00e8s, S., & Yugma, C. (2018). Metaheuristics for the job-shop scheduling problem with machine availability constraints. Computers & Industrial Engineering, 125, 1\u20138. https:\/\/doi.org\/10.1016\/j.cie.2018.08.008","journal-title":"Computers & Industrial Engineering"},{"key":"5592_CR81","doi-asserted-by":"publisher","unstructured":"Tjornfelt-Jensen, M., & Hansen, T. K. (1999). Robust solutions to job shop problems. In Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999, pp. 1138\u20131144. https:\/\/doi.org\/10.1109\/CEC.1999.782551","DOI":"10.1109\/CEC.1999.782551"},{"issue":"2","key":"5592_CR82","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/IMC.1990.687384","volume":"1990","author":"S Tunali","year":"1990","unstructured":"Tunali, S., & Orhun, E. (1990). A knowledge-based production scheduling system. Proceedings of the IEEE International Workshop on Intelligent Motion Control, IMC, 1990(2), 577\u2013580. https:\/\/doi.org\/10.1109\/IMC.1990.687384","journal-title":"Proceedings of the IEEE International Workshop on Intelligent Motion Control, IMC"},{"issue":"21","key":"5592_CR83","doi-asserted-by":"publisher","first-page":"5883","DOI":"10.1080\/00207540601156215","volume":"46","author":"A Upasani","year":"2008","unstructured":"Upasani, A., & Uzsoy, R. (2008). Integrating a decomposition procedure with problem reduction for factory scheduling with disruptions: a simulation study. International Journal of Production Research, 46(21), 5883\u20135905. https:\/\/doi.org\/10.1080\/00207540601156215","journal-title":"International Journal of Production Research"},{"issue":"1","key":"5592_CR84","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.ijpe.2010.08.017","volume":"129","author":"V Vinod","year":"2011","unstructured":"Vinod, V., & Sridharan, R. (2011). Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system. International Journal of Production Economics, 129(1), 127\u2013146.","journal-title":"International Journal of Production Economics"},{"key":"5592_CR85","doi-asserted-by":"publisher","first-page":"104963","DOI":"10.1016\/J.COR.2020.104963","volume":"122","author":"Z Wu","year":"2020","unstructured":"Wu, Z., Sun, S., & Yu, S. (2020). Optimizing makespan and stability risks in job shop scheduling. Computers & Operations Research, 122, 104963. https:\/\/doi.org\/10.1016\/J.COR.2020.104963","journal-title":"Computers & Operations Research"},{"issue":"7","key":"5592_CR86","doi-asserted-by":"publisher","first-page":"2147","DOI":"10.1080\/00207543.2022.2060772","volume":"61","author":"J Xie","year":"2023","unstructured":"Xie, J., Li, X., Gao, L., & Gui, L. (2023). A new neighbourhood structure for job shop scheduling problems. International Journal of Production Research, 61(7), 2147\u20132161. https:\/\/doi.org\/10.1080\/00207543.2022.2060772","journal-title":"International Journal of Production Research"},{"key":"5592_CR87","doi-asserted-by":"publisher","unstructured":"Yahyaoui, A., Fnaiech, N., & Fnaiech, F. (2009). New shifting method for job shop scheduling subject to invariant constraints of resources availability. In IECON Proceedings (Industrial Electronics Conference), pp. 3387\u20133392. https:\/\/doi.org\/10.1109\/IECON.2009.5415368","DOI":"10.1109\/IECON.2009.5415368"},{"key":"5592_CR88","unstructured":"Yamada, T., & Nakano, R. (1992). A genetic algorithm applicable to large-scale job-shop problems. In PPSN (Vol. 2, pp. 281\u2013290)."},{"key":"5592_CR89","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/619254","author":"HA Yang","year":"2014","unstructured":"Yang, H. A., Lv, Y., Xia, C., Sun, S., & Wang, H. (2014). Optimal computing budget allocation for ordinal optimization in solving stochastic job shop scheduling problems. Mathematical Problems in Engineering. https:\/\/doi.org\/10.1155\/2014\/619254","journal-title":"Mathematical Problems in Engineering"},{"issue":"8","key":"5592_CR90","doi-asserted-by":"publisher","first-page":"2449","DOI":"10.1080\/00207540802662896","volume":"48","author":"M Zandieh","year":"2010","unstructured":"Zandieh, M., & Adibi, M. A. (2010). Dynamic job shop scheduling using variable neighbourhood search. International Journal of Production Research, 48(8), 2449\u20132458. https:\/\/doi.org\/10.1080\/00207540802662896","journal-title":"International Journal of Production Research"},{"issue":"11","key":"5592_CR91","doi-asserted-by":"publisher","first-page":"3229","DOI":"10.1016\/j.cor.2005.12.002","volume":"34","author":"C Zhang","year":"2007","unstructured":"Zhang, C., Li, P., Guan, Z., & Rao, Y. (2007). A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem. Computers & Operations Research, 34(11), 3229\u20133242. https:\/\/doi.org\/10.1016\/j.cor.2005.12.002","journal-title":"Computers & Operations Research"},{"key":"5592_CR92","doi-asserted-by":"publisher","first-page":"117460","DOI":"10.1016\/j.eswa.2022.117460","volume":"203","author":"G Zhang","year":"2022","unstructured":"Zhang, G., Lu, X., Liu, X., Zhang, L., Wei, S., & Zhang, W. (2022). An effective two-stage algorithm based on convolutional neural network for the bi-objective flexible job shop scheduling problem with machine breakdown. Expert Systems with Applications, 203, 117460. https:\/\/doi.org\/10.1016\/j.eswa.2022.117460","journal-title":"Expert Systems with Applications"},{"issue":"4","key":"5592_CR93","doi-asserted-by":"publisher","first-page":"1809","DOI":"10.1007\/s10845-017-1350-2","volume":"30","author":"J Zhang","year":"2019","unstructured":"Zhang, J., Ding, G., Zou, Y., Qin, S., & Fu, J. (2019). Review of job shop scheduling research and its new perspectives under Industry 4.0. Journal of Intelligent Manufacturing, 30(4), 1809\u20131830. https:\/\/doi.org\/10.1007\/s10845-017-1350-2","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"9","key":"5592_CR94","doi-asserted-by":"publisher","first-page":"1708","DOI":"10.3390\/e13091708","volume":"13","author":"R Zhang","year":"2011","unstructured":"Zhang, R., & Wu, C. (2011). An artificial bee colony algorithm for the job shop scheduling problem with random processing times. Entropy, 13(9), 1708\u20131729. https:\/\/doi.org\/10.3390\/e13091708","journal-title":"Entropy"},{"issue":"1","key":"5592_CR95","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1080\/09511920903207472","volume":"23","author":"F Zhao","year":"2010","unstructured":"Zhao, F., Hong, Y., Yu, D., Yang, Y., & Zhang, Q. (2010). A hybrid particle swarm optimisation algorithm and fuzzy logic for process planning and production scheduling integration in holonic manufacturing systems. International Journal of Computer Integrated Manufacturing, 23(1), 20\u201339. https:\/\/doi.org\/10.1080\/09511920903207472","journal-title":"International Journal of Computer Integrated Manufacturing"},{"key":"5592_CR96","doi-asserted-by":"publisher","unstructured":"Zhu, L., & Soh, Y. C. (1999). FMS job-shop scheduling under disruptions with consideration of time and sequence deviation. In IEEE International Symposium on Intelligent Control-Proceedings, pp. 138\u2013143. https:\/\/doi.org\/10.1109\/ISIC.1999.796644","DOI":"10.1109\/ISIC.1999.796644"},{"issue":"5","key":"5592_CR97","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/s00170-005-2537-9","volume":"29","author":"Z Zou","year":"2006","unstructured":"Zou, Z., & Li, C. (2006). Integrated and events-oriented job shop scheduling. International Journal of Advanced Manufacturing Technology, 29(5), 551\u2013556. https:\/\/doi.org\/10.1007\/s00170-005-2537-9","journal-title":"International Journal of Advanced Manufacturing Technology"}],"container-title":["Annals of Operations Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-023-05592-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10479-023-05592-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-023-05592-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T16:23:47Z","timestamp":1721060627000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10479-023-05592-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,2]]},"references-count":97,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["5592"],"URL":"https:\/\/doi.org\/10.1007\/s10479-023-05592-z","relation":{},"ISSN":["0254-5330","1572-9338"],"issn-type":[{"value":"0254-5330","type":"print"},{"value":"1572-9338","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,2]]},"assertion":[{"value":"28 October 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 October 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}