How to cite this paper
Jimenez, J., Gonzalez-Neira, E & Zambrano-Rey, G. (2018). An adaptive genetic algorithm for a dynamic single-machine scheduling problem.Management Science Letters , 8(11), 1117-1132.
Refrences
Aytug, H., Lawley, M. A., McKay, K., Mohan, S., & Uzsoy, R. (2005). Executing production sched-ules in the face of uncertainties: A review and some future directions. European Journal of Opera-tional Research, 161(1), 86-110.
Baker, A. D. (1998). A survey of factory control algorithms that can be implemented in a multi-agent heterarchy: dispatching, scheduling, and pull. Journal of Manufacturing Systems, 17(4), 297-320.
Baker, J. E. (1985, July). Adaptive selection methods for genetic algorithms. In Proceedings of an In-ternational Conference on Genetic Algorithms and their applications (pp. 101-111).
Banos, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J. (2011). Optimi-zation methods applied to renewable and sustainable energy: A review. Renewable and Sustainable Energy Reviews, 15(4), 1753-1766.
Barbosa, J., Leitão, P., Adam, E., & Trentesaux, D. (2015). Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution. Computers in Industry, 66, 99-111.
Barbosa, J., Leitão, P., Trentesaux, D., & Adam, E. (2011, November). Enhancing ADACOR with bi-ology insights towards reconfigurable manufacturing systems. In IECON 2011-37th Annual Confer-ence on IEEE Industrial Electronics Society (pp. 2746-2751). IEEE.
Bianchi, L., Dorigo, M., Gambardella, L. M., & Gutjahr, W. J. (2009). A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing, 8(2), 239-287.
Bierwirth, C., & Mattfeld, D. C. (1999). Production scheduling and rescheduling with genetic algo-rithms. Evolutionary computation, 7(1), 1-17.
Borangiu, T., Răileanu, S., Berger, T., & Trentesaux, D. (2015). Switching mode control strategy in manufacturing execution systems. International Journal of Production Research, 53(7), 1950-1963.
Chryssolouris, G., & Subramaniam, V. (2001). Dynamic scheduling of manufacturing job shops using genetic algorithms. Journal of Intelligent Manufacturing, 12(3), 281-293.
Chu, Y., You, F., & Wassick, J. M. (2014). Hybrid method integrating agent-based modeling and heu-ristic tree search for scheduling of complex batch processes. Computers & Chemical Engineering, 60, 277-296.
Cowling, P., & Chakhlevitch, K. (2003, December). Hyperheuristics for managing a large collection of low level heuristics to schedule personnel. In Evolutionary Computation, 2003. CEC'03. The 2003 Congress on (Vol. 2, pp. 1214-1221). IEEE.
ElMaraghy, W., ElMaraghy, H., Tomiyama, T., & Monostori, L. (2012). Complexity in engineering de-sign and manufacturing. CIRP Annals-Manufacturing Technology, 61(2), 793-814.
Halevi, G., & Cunha, P. F. (2007). Self organization shop floor control. In Digital Enterprise Technolo-gy (pp. 107-114). Springer, Boston, MA.
Herrera, F., & Lozano, M. (1996). Adaptation of genetic algorithm parameters based on fuzzy logic controllers. Genetic Algorithms and Soft Computing, 8, 95-125.
Holvoet, T., Weyns, D., & Valckenaers, P. (2009, September). Patterns of delegate mas. In Self-Adaptive and Self-Organizing Systems, 2009. SASO'09. Third IEEE International Conference on (pp. 1-9). IEEE.
Jimenez, J. F., Bekrar, A., Trentesaux, D., Montoya-Torres, J. R., & Leitão, P. (2013, October). State of the art and future trends of optimality and adaptability articulated mechanisms for manufacturing control systems. In Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on (pp. 1265-1270). IEEE.
Jimenez, J. F., Bekrar, A., Trentesaux, D., Zambrano-Rey, G., & Leitão, P. (2015). Governance mecha-nism in control architectures for flexible manufacturing systems.
Jimenez, J. F., Bekrar, A., Zambrano-Rey, G., Trentesaux, D., & Leitão, P. (2017). Pollux: a dynamic hybrid control architecture for flexible job shop systems. International Journal of Production Re-search, 55(15), 4229-4247.
Leitão, P. (2009). Agent-based distributed manufacturing control: A state-of-the-art survey. Engineer-ing Applications of Artificial Intelligence, 22(7), 979-991.
Li, H., Li, Z., Li, L. X., & Hu, B. (2000). A production rescheduling expert simulation system. Europe-an Journal of Operational Research, 124(2), 283-293.
Madureira, A., Ramos, C., & do Carmo Silva, S. (2000). A genetic algorithm for the dynamic single machine scheduling problem. In Advances in Networked Enterprises (pp. 315-324). Springer, Boston, MA.
Naedele, M., Chen, H. M., Kazman, R., Cai, Y., Xiao, L., & Silva, C. V. (2015). Manufacturing execu-tion systems: A vision for managing software development. Journal of Systems and Software, 101, 59-68.
Nie, L., Gao, L., Li, P., & Shao, X. (2013). Reactive scheduling in a job shop where jobs arrive over time. Computers & Industrial Engineering, 66(2), 389-405.
Nie, L., Gao, L., Li, P., & Wang, X. (2011, June). Multi-Objective optimization for dynamic single-machine scheduling. In International Conference in Swarm Intelligence (pp. 1-9). Springer, Berlin, Heidelberg.
Nie, L., Shao, X., Gao, L., & Li, W. (2010). Evolving scheduling rules with gene expression program-ming for dynamic single-machine scheduling problems. The International Journal of Advanced Man-ufacturing Technology, 50(5-8), 729-747.
Norton, N. (1996). Shop-floor control. Manufacturing Engineer, Volume 78, 175 – 178.
Novas, J. M., Van Belle, J., Saint Germain, B., & Valckenaers, P. (2013). A collaborative framework between a scheduling system and a holonic manufacturing execution system. In Service orientation in holonic and multi agent manufacturing and robotics (pp. 3-17). Springer, Berlin, Heidelberg.
Ouelhadj, D., & Petrovic, S. (2009). A survey of dynamic scheduling in manufacturing systems. Jour-nal of Scheduling, 12(4), 417.
Palit, A. K., & Popovic, D. (2006). Computational intelligence in time series forecasting: theory and en-gineering applications. Springer Science & Business Media.
Pan, Y., Zhang, W. X., Gao, T. Y., Ma, Q. Y., & Xue, D. J. (2011, June). An adaptive Genetic Algo-rithm for the Flexible Job-shop Scheduling Problem. In Computer Science and Automation Engineer-ing (CSAE), 2011 IEEE International Conference on (Vol. 4, pp. 405-409). IEEE.
Pinedo, M. L. (2016). Scheduling: theory, algorithms, and systems. Springer.
Pinedo, M. L. (2016). What Lies Ahead?. In Scheduling (pp. 545-554). Springer, Cham.
Smit, S. K., & Eiben, A. E. (2009, May). Comparing parameter tuning methods for evolutionary algo-rithms. In Evolutionary Computation, 2009. CEC'09. IEEE Congress on (pp. 399-406). IEEE.
Smith, J. (1998). Self adaptation in evolutionary algorithms (Doctoral dissertation, University of the West of England).
Srinivas, M., & Patnaik, L. M. (1994). Genetic algorithms: A survey. Computer, 27(6), 17-26.
Tan, Y., & Aufenanger, M. (2011, July). A real-time rescheduling heuristic using decentralized knowledge-based decisions for flexible flow shops with unrelated parallel machines. In Industrial In-formatics (INDIN), 2011 9th IEEE International Conference on (pp. 431-436). IEEE.
Thomas, A., El Haouzi, H., Klein, T., Belmokhtar, S., & Herrera, C. (2009). Architecture de systèmes contrôlés par la produit pour un environnement de juste à temps. Journal Européen des Systèmes Au-tomatisés (JESA), 43(4-5), 513-535.
Trentesaux, D. (2009). Distributed control of production systems. Engineering Applications of Artificial Intelligence, 22(7), 971-978.
Trentesaux, D., & Prabhu, V. V. (2011). Introduction to Shop‐Floor Control. Wiley Encyclopedia of Operations Research and Management Science, 1-9.
Vieira, G. E., Herrmann, J. W., & Lin, E. (2003). Rescheduling manufacturing systems: a framework of strategies, policies, and methods. Journal of scheduling, 6(1), 39-62.
Vlk, M., & Bartak, R. (2015). Replanning in Predictive-reactive Scheduling. Association for the Ad-vancement of Artificial Intelligence.
Wysk, R. A., & Smith, J. S. (1995). A formal functional characterization of shop floor control. Comput-ers and Industrial Engineering, 28(3), 631-644.
Rey, G. Z., Bonte, T., Prabhu, V., & Trentesaux, D. (2014). Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach. Simulation Modelling Practice and Theory, 46, 53-75.
Baker, A. D. (1998). A survey of factory control algorithms that can be implemented in a multi-agent heterarchy: dispatching, scheduling, and pull. Journal of Manufacturing Systems, 17(4), 297-320.
Baker, J. E. (1985, July). Adaptive selection methods for genetic algorithms. In Proceedings of an In-ternational Conference on Genetic Algorithms and their applications (pp. 101-111).
Banos, R., Manzano-Agugliaro, F., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J. (2011). Optimi-zation methods applied to renewable and sustainable energy: A review. Renewable and Sustainable Energy Reviews, 15(4), 1753-1766.
Barbosa, J., Leitão, P., Adam, E., & Trentesaux, D. (2015). Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution. Computers in Industry, 66, 99-111.
Barbosa, J., Leitão, P., Trentesaux, D., & Adam, E. (2011, November). Enhancing ADACOR with bi-ology insights towards reconfigurable manufacturing systems. In IECON 2011-37th Annual Confer-ence on IEEE Industrial Electronics Society (pp. 2746-2751). IEEE.
Bianchi, L., Dorigo, M., Gambardella, L. M., & Gutjahr, W. J. (2009). A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing, 8(2), 239-287.
Bierwirth, C., & Mattfeld, D. C. (1999). Production scheduling and rescheduling with genetic algo-rithms. Evolutionary computation, 7(1), 1-17.
Borangiu, T., Răileanu, S., Berger, T., & Trentesaux, D. (2015). Switching mode control strategy in manufacturing execution systems. International Journal of Production Research, 53(7), 1950-1963.
Chryssolouris, G., & Subramaniam, V. (2001). Dynamic scheduling of manufacturing job shops using genetic algorithms. Journal of Intelligent Manufacturing, 12(3), 281-293.
Chu, Y., You, F., & Wassick, J. M. (2014). Hybrid method integrating agent-based modeling and heu-ristic tree search for scheduling of complex batch processes. Computers & Chemical Engineering, 60, 277-296.
Cowling, P., & Chakhlevitch, K. (2003, December). Hyperheuristics for managing a large collection of low level heuristics to schedule personnel. In Evolutionary Computation, 2003. CEC'03. The 2003 Congress on (Vol. 2, pp. 1214-1221). IEEE.
ElMaraghy, W., ElMaraghy, H., Tomiyama, T., & Monostori, L. (2012). Complexity in engineering de-sign and manufacturing. CIRP Annals-Manufacturing Technology, 61(2), 793-814.
Halevi, G., & Cunha, P. F. (2007). Self organization shop floor control. In Digital Enterprise Technolo-gy (pp. 107-114). Springer, Boston, MA.
Herrera, F., & Lozano, M. (1996). Adaptation of genetic algorithm parameters based on fuzzy logic controllers. Genetic Algorithms and Soft Computing, 8, 95-125.
Holvoet, T., Weyns, D., & Valckenaers, P. (2009, September). Patterns of delegate mas. In Self-Adaptive and Self-Organizing Systems, 2009. SASO'09. Third IEEE International Conference on (pp. 1-9). IEEE.
Jimenez, J. F., Bekrar, A., Trentesaux, D., Montoya-Torres, J. R., & Leitão, P. (2013, October). State of the art and future trends of optimality and adaptability articulated mechanisms for manufacturing control systems. In Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on (pp. 1265-1270). IEEE.
Jimenez, J. F., Bekrar, A., Trentesaux, D., Zambrano-Rey, G., & Leitão, P. (2015). Governance mecha-nism in control architectures for flexible manufacturing systems.
Jimenez, J. F., Bekrar, A., Zambrano-Rey, G., Trentesaux, D., & Leitão, P. (2017). Pollux: a dynamic hybrid control architecture for flexible job shop systems. International Journal of Production Re-search, 55(15), 4229-4247.
Leitão, P. (2009). Agent-based distributed manufacturing control: A state-of-the-art survey. Engineer-ing Applications of Artificial Intelligence, 22(7), 979-991.
Li, H., Li, Z., Li, L. X., & Hu, B. (2000). A production rescheduling expert simulation system. Europe-an Journal of Operational Research, 124(2), 283-293.
Madureira, A., Ramos, C., & do Carmo Silva, S. (2000). A genetic algorithm for the dynamic single machine scheduling problem. In Advances in Networked Enterprises (pp. 315-324). Springer, Boston, MA.
Naedele, M., Chen, H. M., Kazman, R., Cai, Y., Xiao, L., & Silva, C. V. (2015). Manufacturing execu-tion systems: A vision for managing software development. Journal of Systems and Software, 101, 59-68.
Nie, L., Gao, L., Li, P., & Shao, X. (2013). Reactive scheduling in a job shop where jobs arrive over time. Computers & Industrial Engineering, 66(2), 389-405.
Nie, L., Gao, L., Li, P., & Wang, X. (2011, June). Multi-Objective optimization for dynamic single-machine scheduling. In International Conference in Swarm Intelligence (pp. 1-9). Springer, Berlin, Heidelberg.
Nie, L., Shao, X., Gao, L., & Li, W. (2010). Evolving scheduling rules with gene expression program-ming for dynamic single-machine scheduling problems. The International Journal of Advanced Man-ufacturing Technology, 50(5-8), 729-747.
Norton, N. (1996). Shop-floor control. Manufacturing Engineer, Volume 78, 175 – 178.
Novas, J. M., Van Belle, J., Saint Germain, B., & Valckenaers, P. (2013). A collaborative framework between a scheduling system and a holonic manufacturing execution system. In Service orientation in holonic and multi agent manufacturing and robotics (pp. 3-17). Springer, Berlin, Heidelberg.
Ouelhadj, D., & Petrovic, S. (2009). A survey of dynamic scheduling in manufacturing systems. Jour-nal of Scheduling, 12(4), 417.
Palit, A. K., & Popovic, D. (2006). Computational intelligence in time series forecasting: theory and en-gineering applications. Springer Science & Business Media.
Pan, Y., Zhang, W. X., Gao, T. Y., Ma, Q. Y., & Xue, D. J. (2011, June). An adaptive Genetic Algo-rithm for the Flexible Job-shop Scheduling Problem. In Computer Science and Automation Engineer-ing (CSAE), 2011 IEEE International Conference on (Vol. 4, pp. 405-409). IEEE.
Pinedo, M. L. (2016). Scheduling: theory, algorithms, and systems. Springer.
Pinedo, M. L. (2016). What Lies Ahead?. In Scheduling (pp. 545-554). Springer, Cham.
Smit, S. K., & Eiben, A. E. (2009, May). Comparing parameter tuning methods for evolutionary algo-rithms. In Evolutionary Computation, 2009. CEC'09. IEEE Congress on (pp. 399-406). IEEE.
Smith, J. (1998). Self adaptation in evolutionary algorithms (Doctoral dissertation, University of the West of England).
Srinivas, M., & Patnaik, L. M. (1994). Genetic algorithms: A survey. Computer, 27(6), 17-26.
Tan, Y., & Aufenanger, M. (2011, July). A real-time rescheduling heuristic using decentralized knowledge-based decisions for flexible flow shops with unrelated parallel machines. In Industrial In-formatics (INDIN), 2011 9th IEEE International Conference on (pp. 431-436). IEEE.
Thomas, A., El Haouzi, H., Klein, T., Belmokhtar, S., & Herrera, C. (2009). Architecture de systèmes contrôlés par la produit pour un environnement de juste à temps. Journal Européen des Systèmes Au-tomatisés (JESA), 43(4-5), 513-535.
Trentesaux, D. (2009). Distributed control of production systems. Engineering Applications of Artificial Intelligence, 22(7), 971-978.
Trentesaux, D., & Prabhu, V. V. (2011). Introduction to Shop‐Floor Control. Wiley Encyclopedia of Operations Research and Management Science, 1-9.
Vieira, G. E., Herrmann, J. W., & Lin, E. (2003). Rescheduling manufacturing systems: a framework of strategies, policies, and methods. Journal of scheduling, 6(1), 39-62.
Vlk, M., & Bartak, R. (2015). Replanning in Predictive-reactive Scheduling. Association for the Ad-vancement of Artificial Intelligence.
Wysk, R. A., & Smith, J. S. (1995). A formal functional characterization of shop floor control. Comput-ers and Industrial Engineering, 28(3), 631-644.
Rey, G. Z., Bonte, T., Prabhu, V., & Trentesaux, D. (2014). Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach. Simulation Modelling Practice and Theory, 46, 53-75.