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All issues Volume 55 (2021) Supplement RAIRO-Oper. Res., 55 (2021) S2125-S2159 References
Free Access
Issue
RAIRO-Oper. Res.
Volume 55, 2021
Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
Page(s) S2125 - S2159
DOI https://doi.org/10.1051/ro/2020077
Published online 02 March 2021
  • J. Acevedo and G. Mejía, Programación reactiva y robusta de la producción en un ambiente sistema de manufactura flexible: llegada de nuevas órdenes y cambios en la prioridad de las órdenes de trabajo. Maestria, Departamento de Ingeniería Industrial, Universidad de los Andes (2006). [Google Scholar]
  • N. Al-Hinai and T. El-Mekkawy, An efficient hybridized genetic algorithm architecture for the flexible job shop scheduling problem. Flexible Serv. Manuf. J. 23 (2011) 64–85. [Google Scholar]
  • Ö. Başak and Y.E. Albayrak, Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems. Comput. Ind. Eng. 86 (2015) 116–126. [Google Scholar]
  • O.T. Baruwa, M.A. Piera and A. Guasch, Deadlock-free scheduling method for flexible manufacturing systems based on timed colored Petri nets and anytime heuristic search. IEEE Trans. Syst. Man Cybern. 45 (2014) 831–846. [Google Scholar]
  • J.A. Chedid, K.S. Navarro, H.O. Mateus and A.S. Mercado, Reprogramación de producción en cadenas de suministro colaborativas: Una revisión de la literatura. Espacio 38 (2017) 23. [Google Scholar]
  • F. Chen and J. Chen, Performance modelling and evaluation of dynamic tool allocation in flexible manufacturing systems using coloured Petri nets: an object-oriented approach. Int. J. Adv. Manuf. Technol. 21 (2003) 98–109. [Google Scholar]
  • J. Chen and F.F. Chen, Adaptive scheduling in random flexible manufacturing systems subject to machine breakdowns. Int. J. Prod. Res. 41 (2003) 1927–1951. [Google Scholar]
  • H. Cho, Petri net models for message manipulation and event monitoring in an FMS cell. Int. J. Prod. Res. 36 (1998) 231–250. [Google Scholar]
  • C. Cotta, L. Mathieson and P. Moscato, Memetic algorithms. In: Handbook of Heuristics edited by R. Martí, P. M. Pardalos, M. G. C. Resende. Springer, Cham (2018) 607–638. [Google Scholar]
  • B.K. Dey, S. Pareek, M. Tayyab and B. Sarkar, Autonomation policy to control work-in-process inventory in a smart production system. Int. J. Prod. Res. (2020) 1–23. DOI: 10.1080/00207543.2020.1722325. [Google Scholar]
  • J. Dorn, R. Kerr and G. Thalhammer, Reactive scheduling: improving the robustness of schedules and restricting the effects of shop floor disturbances by fuzzy reasoning. Int. J. Human-Comput. Stud. 42 (1995) 687–704. [Google Scholar]
  • H.A. Elmaraghy and T.Y. Elmekkawy, Deadlock-free rescheduling in flexible manufacturing systems. CIRP Ann. 51 (2002) 371–374. [Google Scholar]
  • M.R. Garey, D.S. Johnson and R. Sethi, The complexity of flowshop and jobshop scheduling. Math. Oper. Res. 1 (1976) 117–129. [Google Scholar]
  • P. Garg, A comparison between Memetic algorithm and Genetic algorithm for the cryptanalysis of simplified data encryption standard algorithm. Int. J. Network Secur. App. 1 (2009) 34–42. [Google Scholar]
  • A. Gholami, R. Sheikh, N. Mizani and S.S. Sana, ABC analysis of the customers using axiomatic design and incomplete rough set. RAIRO:OR 52 (2018) 1219–1232. [Google Scholar]
  • R. Guchhait, B.K. Dey, S. Bhuniya, B. Ganguly, B. Mandal, R.K. Bachar, B. Sarkar, H.M. Wee and K. Chaudhuri, Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages. RAIRO:OR 54 (2020) 251–266. [Google Scholar]
  • L. Han, K. Xing, X. Chen, H. Lei and F. Wang, Deadlock-free genetic scheduling for flexible manufacturing systems using Petri nets and deadlock controllers. Int. J. Prod. Res. 52 (2014) 1557–1572. [Google Scholar]
  • L. Han, K. Xing, X. Chen and F. Xiong, A Petri net-based particle swarm optimization approach for scheduling deadlock-prone flexible manufacturing systems. J. Intel. Manuf. 29 (2018) 1083–1096. [Google Scholar]
  • S.K. Hasan, R. Sarker and D. Essam, Genetic algorithm for job-shop scheduling with machine unavailability and breakdowns. Int. J. Prod. Res. 49 (2011) 4999–5015. [Google Scholar]
  • I. Hatono, K. Yamagata and H. Tamura, Modeling and online scheduling of flexible manufacturing systems using stochastic Petri nets. IEEE Trans. Softw. Eng. 17 (1991) 126–132. [Google Scholar]
  • H. Hoos and T. Stutzle, Stochastic Local Search: Foundations and Applications. Morgan Kaufmann Publishers, San Francisco, CA (2005). [Google Scholar]
  • B. Huang, Z. Cai, M. Zhou and J. Hao, Scheduling of FMS based on binary decision diagram and Petri net. In: IEEE 15th International Conference on Networking, Sensing and Control (ICNSC). (2018) 1–6. [Google Scholar]
  • G. Jamali, S.S. Sana and R. Moghdani, Hybrid improved cuckoo search algorithm and genetic algorithm for solving markov-modulated demand. RAIRO:OR 52 (2018) 473–497. [Google Scholar]
  • A. Khanna, P. Gautam, B. Sarkar and C.K. Jaggi, Integrated vendor–buyer strategies for imperfect production systems with maintenance and warranty policy. RAIRO:OR 54 (2020) 435–450. [Google Scholar]
  • Y.W. Kim, T. Suzuki and T. Narikiyo, FMS scheduling based on timed Petri Net model and reactive graph search. Appl. Math. Modell. 31 (2007) 955–970. [Google Scholar]
  • S. Kirkpatrick, C.D. Gelatt and M.P. Vecchi, Optimization by simulated annealing. Science 220 (1983) 671–680. [Google Scholar]
  • R.R. Kumar, A.K. Singh and M. Tiwari, A fuzzy based algorithm to solve the machine-loading problems of a FMS and its neuro fuzzy Petri net model. Int. J. Adv. Manuf. Technol. 23 (2004) 318–341. [Google Scholar]
  • B.S. Kumar, G.J. Raju and G.R. Janardhana, Production planning in flexible manufacturing system by considering the multi-objective functions. In: Advances in Materials and Manufacturing Engineering. Lecture Notes in Mechanical Engineering. (ICAMME 2019) Springer, Singapore (2020) 343–352. [Google Scholar]
  • H. Lei, K. Xing, L. Han and Z. Gao, Hybrid heuristic search approach for deadlock-free scheduling of flexible manufacturing systems using Petri nets. Appl. Soft Comput. 55 (2017) 413–423. [Google Scholar]
  • C. Li, W. Wu, Y. Feng and G. Rong, Scheduling FMS problems with heuristic search function and transition-timed Petri nets. J. Intell. Manuf. 26 (2015) 933–944. [Google Scholar]
  • C. Low and T.H. Wu, Mathematical modelling and heuristic approaches to operation scheduling problems in an FMS environment. Int. Jo. Prod. Res. 39 (2001) 689–708. [Google Scholar]
  • D.R. Mahapatra, S. Panda and S.S. Sana, Multi-choice and stochastic programming for transportation problem involved in supply of foods and medicines to hospitals with consideration of logistic distribution. RAIRO:OR 54 (2020) 1119–1132. [Google Scholar]
  • S.V. Mehta, Predictable scheduling of a single machine subject to breakdowns. Int. J. Comput. Integr. Manuf. 12 (1999) 15–38. [Google Scholar]
  • G. Mejia and J. Acevedo, Reactive scheduling in FMS: an integrated approach based on petri nets, genetic algorithms and simulation. In: Third International Conference on Production Research, Americas’ Region (2006). [Google Scholar]
  • G. Mejía and K. Niño, A new Hybrid Filtered Beam Search algorithm for deadlock-free scheduling of flexible manufacturing systems using Petri Nets. Comput. Ind. Eng. 108 (2017) 165–176. [Google Scholar]
  • U. Mishra, J.Z. Wu and B. Sarkar, A sustainable production-inventory model for a controllable carbon emissions rate under shortages. J. Cleaner Prod. 256 (2020) 120268. [Google Scholar]
  • P. Moscato and C. Cotta, Una introducción a los algoritmos meméticos. Intel. Artif. Rev. Iberoamericana Intel. Artif. 7 (2003) 131–148. [Google Scholar]
  • T. Murata, Petri nets: properties, analysis and applications. Proc. IEEE 77 (1989) 541–580. [Google Scholar]
  • H.Z. Nabi and T. Aized, Performance evaluation of a carousel configured multiple products flexible manufacturing system using Petri net. Oper. Manag. Res. 13 (2020) 109–129. [Google Scholar]
  • K.S. Navarro, J.A. Chedid, G.M. Arquez, W.F. Florez, H.O. Mateus, S.S. Sana and L.E. Cárdenas-Barrón, An EPQ inventory model considering an imperfect production system with probabilistic demand and collaborative approach. J. Adv. Manage. Res. 17 (2019) 282–304. [Google Scholar]
  • K.S. Navarro, J.A. Chedid, W.F. Florez, H.O. Mateus, L.E. Cárdenas-Barrón and S.S. Sana, A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand. J. Ind. Manage. Optim. 16 (2020) 1613–1633. [Google Scholar]
  • P.S. Pachpor, R. Shrivastava, D. Seth and S. Pokharel, Application of Petri nets towards improved utilization of machines in job shop manufacturing environments. J. Manuf. Technol. Manage. 28 (2017) 169–188. [Google Scholar]
  • A.M. Patel and A.Y. Joshi, Modeling and analysis of a manufacturing system with deadlocks to generate the reachability tree using Petri net system. Proc. Eng. 64 (2013) 775–784. [Google Scholar]
  • M. Pinedo, Scheduling. Springer, Cham (2012). [Google Scholar]
  • M. Pinedo, Planning and Scheduling in Manufacturing and Services. Springer, New York, NY (2005). [Google Scholar]
  • S.S. Sana, H. Ospina-Mateus, F.G. Arrieta and J.A. Chedid, Application of genetic algorithm to job scheduling under ergonomic constraints in manufacturing industry. J. Ambient Intell. Humanized Comput. 10 (2019) 2063–2090. [Google Scholar]
  • S.S. Sankar, S. Ponnanbalam and C. Rajendran, A multiobjective genetic algorithm for scheduling a flexible manufacturing system. Int. J. Adv. Manuf. Technol. 22 (2003) 229–236. [Google Scholar]
  • S.S. Sankar, S. Ponnambalam and M. Gurumarimuthu, Scheduling flexible manufacturing systems using parallelization of multi-objective evolutionary algorithms. Int. J. Adv. Manuf. Technol. 30 (2006) 279–285. [Google Scholar]
  • B. Santosa, R. Damayanti and B. Sarkar, Solving multi-product inventory ship routing with a heterogeneous fleet model using a hybrid cross entropy-genetic algorithm: a case study in Indonesia Prod. Manuf. Res. 4 (2016) 90–113. [Google Scholar]
  • N. Saxena, B. Sarkar and S. Singh, Selection of remanufacturing/production cycles with an alternative market: a perspective on waste management. J. Cleaner Prod. 245 (2020) 118935. [Google Scholar]
  • B.K. Sett, S. Sarkar and B. Sarkar, Optimal buffer inventory and inspection errors in an imperfect production system with preventive maintenance. Int. J. Adv. Manuf. Technol. 90 (2017) 545–560. [Google Scholar]
  • M. Souier, M. Dahane and F. Maliki, An NSGA-II-based multiobjective approach for real-time routing selection in a flexible manufacturing system under uncertainty and reliability constraints. Int. J. Adv. Manuf. Technol. 100 (2019) 2813–2829. [Google Scholar]
  • A.A. Taleizadeh, L.E. Cárdenas-Barrón and B. Mohammadi, A deterministic multi product single machine EPQ model with backordering, scraped products, rework and interruption in manufacturing process. Int. J. Prod. Econ. 150 (2014) 9–27. [Google Scholar]
  • Y. Tanimizu, T. Sakaguchi, K. Iwamura and N. Sugimura, Evolutional reactive scheduling for agile manufacturing systems. Int. J. Prod. Res. 44 (2006) 3727–3742. [Google Scholar]
  • E.S. Tashnizi, S. Farahani and A.F. Nahrekhalaji, Production process optimization in flexible manufacturing system using Petri nets. In: Proceedings of the World Congress on Engineering and Computer Science (2008) 22–24. [Google Scholar]
  • M. Tayyab, J. Jemai, H. Lim and B. Sarkar, A sustainable development framework for a cleaner multi-item multi-stage textile production system with a process improvement initiative. J. Cleaner Prod. 246 (2020) 119055. [Google Scholar]
  • S. Tian, T. Wang, L. Zhang and X. Wu, Real-time shop floor scheduling method based on virtual queue adaptive control: algorithm and experimental results. Measurement 147 (2019) 106689. [Google Scholar]
  • F. Tüysüz and C. Kahraman, Modeling a flexible manufacturing cell using stochastic Petri nets with fuzzy parameters. Expert Syst. App. 37 (2010) 3910–3920. [Google Scholar]
  • M. Ullah and B. Sarkar, Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality. Int. J. Prod. Econ. 219 (2020) 360–374. [Google Scholar]
  • G.E. Vieira, J.W. Herrmann and E. Lin, Rescheduling manufacturing systems: a framework of strategies, policies, and methods. J. Schedul. 6 (2003) 39–62. [Google Scholar]
  • Z. Zhao, G. Zhang and Z. Bing, Scheduling optimization for FMS based on Petri net modeling and GA. In: IEEE International Conference on Automation and Logistics (ICAL) (2011) 422–427. [Google Scholar]

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