How to cite this paper
Touil, A., Echchtabi, A., Bellabdaoui, A & Charkaoui, A. (2016). A hybrid metaheuristic method to optimize the order of the sequences in continuous-casting.International Journal of Industrial Engineering Computations , 7(3), 385-398.
Refrences
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Allahverdi, A., & Al-Anzi, F. S. (2006). Scheduling multi-stage parallel-processor services to minimize average response time. Journal of the Operational Research Society, 57(1), 101-110.
Allaoui, H., & Artiba, A. (2004). Integrating simulation and optimization to schedule a hybrid flow shop with maintenance constraints. Computers & Industrial Engineering, 47(4), 431-450.
Atighehchian, A., Bijari, M., & Tarkesh, H. (2009). A novel hybrid algorithm for scheduling steel-making continuous casting production. Computers & Operations Research, 36(8), 2450-2461.
Bandyopadhyay, S., Saha, S., Maulik, U., & Deb, K. (2008). A simulated annealing-based multiobjective optimization algorithm: AMOSA. Evolutionary Computation, IEEE Transactions on, 12(3), 269-283.
Bellabdaoui, A., & Teghem, J. (2006). A mixed-integer linear programming model for the continuous casting planning. International Journal of Production Economics, 104(2), 260-270.
Bellabdaoui, A., Fiordaliso, A., & Teghem, J. (2005). A heuristic algorithm for scheduling the steelmaking continuous casting process. Pacific Journal of Optimization, 1(3), 447-464.
Bertel, S., & Billaut, J. C. (2004). A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation. European Journal of Operational Research, 159(3), 651-662.
Chokshi, N. N., Matson, J. B., & McFarlane, D. C. (2000). Distributed co-ordination of steel-making operations for reduced production stoppages.Proceedings of MCPL.
Czapi?ski, M. (2010). Parallel simulated annealing with genetic enhancement for flowshop problem with C sum. Computers & Industrial Engineering, 59(4), 778-785.
Figielska, E. (2009). A genetic algorithm and a simulated annealing algorithm combined with column generation technique for solving the problem of scheduling in the hybrid flowshop with additional resources. Computers & Industrial Engineering, 56(1), 142-151.
Haouari, M., & M & apos; Hallah, R. (1997). Heuristic algorithms for the two-stage hybrid flowshop problem. Operations research letters, 21(1), 43-53.
Janiak, A., Kozan, E., Lichtenstein, M., & O?uz, C. (2007). Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion. International journal of production economics, 105(2), 407-424.
Kahraman, C., Engin, O., Kaya, I., & Kerim Yilmaz, M. (2008). An application of effective genetic algorithms for solving hybrid flow shop scheduling problems. International Journal of Computational Intelligence Systems, 1(2), 134-147.
Kumar, V., Kumar, S., Tiwari, M. K., & Chan, F. T. S. (2006). Auction-based approach to resolve the scheduling problem in the steel making process.International journal of production research, 44(8), 1503-1522.
Kurz, M. E., & Askin, R. G. (2004). Scheduling flexible flow lines with sequence-dependent setup times. European Journal of Operational Research, 159(1), 66-82.
Laha, D., & Chakraborty, U. K. (2009). An efficient hybrid heuristic for makespan minimization in permutation flow shop scheduling. The International Journal of Advanced Manufacturing Technology, 44(5-6), 559-569.
Low, C. (2005). Simulated annealing heuristic for flow shop scheduling problems with unrelated parallel machines. Computers & Operations Research, 32(8), 2013-2025.
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. The journal of chemical physics, 21(6), 1087-1092.
Naderi, B., Zandieh, M., Balagh, A. K. G., & Roshanaei, V. (2009). An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert systems with Applications, 36(6), 9625-9633.
Nawaz, M., Enscore, E. E., & Ham, I. (1983). A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, 11(1), 91-95.
Nearchou, A. C. (2004). Flow-shop sequencing using hybrid simulated annealing. Journal of Intelligent manufacturing, 15(3), 317-328.
Pacciarelli, D., & Pranzo, M. (2004). Production scheduling in a steelmaking-continuous casting plant. Computers & Chemical Engineering, 28(12), 2823-2835.
Pan, Q. K., Wang, L., Mao, K., Zhao, J. H., & Zhang, M. (2013). An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. Automation Science and Engineering, IEEE Transactions on, 10(2), 307-322.
Reeves, C. R. (1995). A genetic algorithm for flowshop sequencing.Computers & operations research, 22(1), 5-13.
Ruiz, R., & Maroto, C. (2006). A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. European Journal of Operational Research, 169(3), 781-800.
Ruiz, R., & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033-2049.
Sadegheih, A. (2006). Scheduling problem using genetic algorithm, simulated annealing and the effects of parameter values on GA performance. Applied Mathematical Modelling, 30(2), 147-154.
Sanvicente-S?nchez, H., & Frausto-Sol?s, J. (2004). A method to establish the cooling scheme in simulated annealing like algorithms. In Computational Science and Its Applications–ICCSA 2004 (pp. 755-763). Springer Berlin Heidelberg.
Shiau, D. F., Cheng, S. C., & Huang, Y. M. (2008). Proportionate flexible flow shop scheduling via a hybrid constructive genetic algorithm. Expert Systems with Applications, 34(2), 1133-1143.
Slotnick, S. A. (2011). Optimal and heuristic lead-time quotation for an integrated steel mill with a minimum batch size. European Journal of Operational Research, 210(3), 527-536.
Tang, L., Liu, J., Rong, A., & Yang, Z. (2000). A mathematical programming model for scheduling steelmaking-continuous casting production. European Journal of Operational Research, 120(2), 423-435.
Xuan, H., & Tang, L. (2007). Scheduling a hybrid flowshop with batch production at the last stage. Computers & Operations Research, 34(9), 2718-2733.
Xujun, Z., & Zhimin, L. (2009, July). Model and solution for steelmaking-continuous casting scheduling problem based on constraint programming method. In Information Technology and Computer Science, 2009. ITCS 2009. International Conference on (Vol. 1, pp. 19-22). IEEE.
Zhang, Y., Li, X., & Wang, Q. (2009). Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization.European Journal of Operational Research, 196(3), 869-876.
Allahverdi, A., & Al-Anzi, F. S. (2006). Scheduling multi-stage parallel-processor services to minimize average response time. Journal of the Operational Research Society, 57(1), 101-110.
Allaoui, H., & Artiba, A. (2004). Integrating simulation and optimization to schedule a hybrid flow shop with maintenance constraints. Computers & Industrial Engineering, 47(4), 431-450.
Atighehchian, A., Bijari, M., & Tarkesh, H. (2009). A novel hybrid algorithm for scheduling steel-making continuous casting production. Computers & Operations Research, 36(8), 2450-2461.
Bandyopadhyay, S., Saha, S., Maulik, U., & Deb, K. (2008). A simulated annealing-based multiobjective optimization algorithm: AMOSA. Evolutionary Computation, IEEE Transactions on, 12(3), 269-283.
Bellabdaoui, A., & Teghem, J. (2006). A mixed-integer linear programming model for the continuous casting planning. International Journal of Production Economics, 104(2), 260-270.
Bellabdaoui, A., Fiordaliso, A., & Teghem, J. (2005). A heuristic algorithm for scheduling the steelmaking continuous casting process. Pacific Journal of Optimization, 1(3), 447-464.
Bertel, S., & Billaut, J. C. (2004). A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation. European Journal of Operational Research, 159(3), 651-662.
Chokshi, N. N., Matson, J. B., & McFarlane, D. C. (2000). Distributed co-ordination of steel-making operations for reduced production stoppages.Proceedings of MCPL.
Czapi?ski, M. (2010). Parallel simulated annealing with genetic enhancement for flowshop problem with C sum. Computers & Industrial Engineering, 59(4), 778-785.
Figielska, E. (2009). A genetic algorithm and a simulated annealing algorithm combined with column generation technique for solving the problem of scheduling in the hybrid flowshop with additional resources. Computers & Industrial Engineering, 56(1), 142-151.
Haouari, M., & M & apos; Hallah, R. (1997). Heuristic algorithms for the two-stage hybrid flowshop problem. Operations research letters, 21(1), 43-53.
Janiak, A., Kozan, E., Lichtenstein, M., & O?uz, C. (2007). Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion. International journal of production economics, 105(2), 407-424.
Kahraman, C., Engin, O., Kaya, I., & Kerim Yilmaz, M. (2008). An application of effective genetic algorithms for solving hybrid flow shop scheduling problems. International Journal of Computational Intelligence Systems, 1(2), 134-147.
Kumar, V., Kumar, S., Tiwari, M. K., & Chan, F. T. S. (2006). Auction-based approach to resolve the scheduling problem in the steel making process.International journal of production research, 44(8), 1503-1522.
Kurz, M. E., & Askin, R. G. (2004). Scheduling flexible flow lines with sequence-dependent setup times. European Journal of Operational Research, 159(1), 66-82.
Laha, D., & Chakraborty, U. K. (2009). An efficient hybrid heuristic for makespan minimization in permutation flow shop scheduling. The International Journal of Advanced Manufacturing Technology, 44(5-6), 559-569.
Low, C. (2005). Simulated annealing heuristic for flow shop scheduling problems with unrelated parallel machines. Computers & Operations Research, 32(8), 2013-2025.
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. The journal of chemical physics, 21(6), 1087-1092.
Naderi, B., Zandieh, M., Balagh, A. K. G., & Roshanaei, V. (2009). An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert systems with Applications, 36(6), 9625-9633.
Nawaz, M., Enscore, E. E., & Ham, I. (1983). A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, 11(1), 91-95.
Nearchou, A. C. (2004). Flow-shop sequencing using hybrid simulated annealing. Journal of Intelligent manufacturing, 15(3), 317-328.
Pacciarelli, D., & Pranzo, M. (2004). Production scheduling in a steelmaking-continuous casting plant. Computers & Chemical Engineering, 28(12), 2823-2835.
Pan, Q. K., Wang, L., Mao, K., Zhao, J. H., & Zhang, M. (2013). An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. Automation Science and Engineering, IEEE Transactions on, 10(2), 307-322.
Reeves, C. R. (1995). A genetic algorithm for flowshop sequencing.Computers & operations research, 22(1), 5-13.
Ruiz, R., & Maroto, C. (2006). A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. European Journal of Operational Research, 169(3), 781-800.
Ruiz, R., & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033-2049.
Sadegheih, A. (2006). Scheduling problem using genetic algorithm, simulated annealing and the effects of parameter values on GA performance. Applied Mathematical Modelling, 30(2), 147-154.
Sanvicente-S?nchez, H., & Frausto-Sol?s, J. (2004). A method to establish the cooling scheme in simulated annealing like algorithms. In Computational Science and Its Applications–ICCSA 2004 (pp. 755-763). Springer Berlin Heidelberg.
Shiau, D. F., Cheng, S. C., & Huang, Y. M. (2008). Proportionate flexible flow shop scheduling via a hybrid constructive genetic algorithm. Expert Systems with Applications, 34(2), 1133-1143.
Slotnick, S. A. (2011). Optimal and heuristic lead-time quotation for an integrated steel mill with a minimum batch size. European Journal of Operational Research, 210(3), 527-536.
Tang, L., Liu, J., Rong, A., & Yang, Z. (2000). A mathematical programming model for scheduling steelmaking-continuous casting production. European Journal of Operational Research, 120(2), 423-435.
Xuan, H., & Tang, L. (2007). Scheduling a hybrid flowshop with batch production at the last stage. Computers & Operations Research, 34(9), 2718-2733.
Xujun, Z., & Zhimin, L. (2009, July). Model and solution for steelmaking-continuous casting scheduling problem based on constraint programming method. In Information Technology and Computer Science, 2009. ITCS 2009. International Conference on (Vol. 1, pp. 19-22). IEEE.
Zhang, Y., Li, X., & Wang, Q. (2009). Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization.European Journal of Operational Research, 196(3), 869-876.