A genetic algorithm for the steel continuous casting with inter-sequence dependent setups and dedicated machines
RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 4-5, pp. 1351-1376.

The steel continuous casting planning and scheduling problem namely SCC is a particular hybrid (flexible) flowshop that includes stages: (i) the converters (CV), (ii) the refining stands (RS) and (iii) the continuous casting (CC) stages. In this paper we study the SCC with inter-sequence dependent setups and dedicated machines at the last stage. The batch sequences are assumed to be pre-determined for one of the CC devices with a non preemptive scheduling process. The aim is to schedule the batches for each CC machine including the times setup between two successive sequences. We model the problem as a MILP where the objective is to minimize the makespan Cmax that we formulate as the largest completion time taking account of the setup times for each CC. Then, we propose an adapted genetic algorithm that we call Regeneration GA (RGA) to solve the problem. We use a randomly generated instances of several sizes to test the model and for which we do not know an optimal solution. The method is able to solve the problems in an acceptable time for medium and large instances while a commercial solver was able to solve only small size instances.

DOI : 10.1051/ro/2018023
Classification : 90B35, 90B50, 90C11, 90C59
Mots-clés : SCC, GA, scheduling, Cmax, setup
Sbihi, Abdelkader 1 ; Chemangui, Makram 1

1
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     title = {A genetic algorithm for the steel continuous casting with inter-sequence dependent setups and dedicated machines},
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Sbihi, Abdelkader; Chemangui, Makram. A genetic algorithm for the steel continuous casting with inter-sequence dependent setups and dedicated machines. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 4-5, pp. 1351-1376. doi : 10.1051/ro/2018023. http://www.numdam.org/articles/10.1051/ro/2018023/

[1] A. Atighehchian, M. Bijari and H. Tarkesh, A novel hybrid algorithm for scheduling steelmaking continuous casting production. Comput. Oper. Res. 36 (2009) 2450–2461. | DOI | Zbl

[2] S. Basu and G. Dutta, A Survey of the Non-Optimization techniques used in an integrated steel plant. Manag. Dyn. 6 (2006) 33–68.

[3] A. Bellabdaoui and J. Teghem, A mixed-integer linear programming model for the continuous casting planning. Int. J. Prod. Econom. 104 (2006) 260–270. | DOI

[4] A. Bellabdaoui, A. Fiordaliso and J. Teghem, A heuristic algorithm for scheduling the steelmaking continuous casting process. Pac. J. Optim. 1 (2005) 447–464. | MR | Zbl

[5] J. Blazewicz, K. Ecker, E. Pesch, G. Schmidt and J. Weglarz, Scheduling Computer Manufacturing Processes. Springer (1996). | DOI | Zbl

[6] N. Chakraborti, R. Kumar and D. Jain, A study of the continuous casting mold using a pareto-converging genetic algorithm. Appl. Math. Model. 25 (2001) 287–297. | DOI | Zbl

[7] P.C. Chang and S.H. Chen, Integrating Dominance Properties with Genetic Algorithms for Parallel Machine Scheduling Problems with Setup Times. Appl. Soft Comput. 11 (2011) 1263–1274. | DOI

[8] L. Chen, N. Bostel, P. Dejax, J.C. Cai and L.F. Xi, A tabu search algorithm for the integrated scheduling problem of container handling systems in a maritime terminal. Eur. J. Oper. Res. 181 (2007) 40–58. | DOI | MR | Zbl

[9] P.I. Cowling, D. Ouelhadj and S. Petrovic, Dynamic scheduling of steel casting and mill using multi-agents. Prod. Plan. Control 15 (2004) 495–501. | DOI

[10] B. De Schutter, Designing optimal timing and sequencing strategies for a continuous steel foundry, in Proceedings of the European Control Conference 1999 (ECC’99), Karlsruhe, Germany, Paper 160/BP–2.6, Aug.–Sept. (1999). | DOI

[11] G. Dutta and R. Fourer, A survey of mathematical programming application in integrated steel plants. Manuf. Service Oper. Manag. 3 (2001) 387–400. | DOI

[12] I. Ferretti, S. Zanoni and L. Zavanella, Production-inventory scheduling using ant system metaheuristic. Int. J. Prod. Econom. 104 (2008) 317–326. | DOI

[13] M. Garey and D. Johnson, Computers and Intractability: A Guide to the Theory of Np-Completness. W.H. Freeman and Company, San Francisco (1979). | MR | Zbl

[14] J.N.D. Gupta, Two-stage, hybrid flowshop scheduling problem. J. Oper. Res. Soc. 39 (1988) 359–364. | DOI | Zbl

[15] I. Harjunkoski and I.E. Grossmann, A decomposition approach for the scheduling of a steel plant production. Comput. Chem. Eng. 25 (2001) 1647–1660. | DOI

[16] M. Helal,G. Rabadi and A. Al-Salem, A tabu search algorithm to minimize the makespan for the unrelated parallel machines scheduling problem with setup times. Int. J. Oper. Res. 3 (2006) 182–192. | MR | Zbl

[17] J.R. Kalagnanam, M.W. Dawande, M. Trumbo and H.S. Lee, The surplus inventory matching problem in the process industry. Oper. Res. 48 (2000) 505–516. | DOI

[18] C.-H. Ko and S.-F. Wang, Precast production scheduling using multi-objective genetic algorithms. Expert Syst. Appl. 38 (2011) 8293–8302. | DOI

[19] H.S. Lee,S.S. Murthy, S.W. Haider and D.V. Morse, Primary production scheduling at steelmaking industries. IBM J. Res. Develop 40 (1996) 231–252. | DOI

[20] K. Lee, S.Y. Chang and Y. Hong, Continuous slab caster scheduling and interval graphs. Prod. Plan. Control 15 (2004) 495–501. | DOI

[21] L. Li, Q. Tang, P. Peng Zheng, L. Zhang and C.A. Floudas, An improved self-adaptive genetic algorithm for scheduling steel-making continuous casting production, in Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2015), Core Theory and Applications of Industrial Engineering, 1: 399–410, Tianjin, July 25–26th (2015).

[22] R. Linn and W. Zhang, Hybrid flow shop scheduling: a survey. Comput. Ind. Eng. 31 (1999) 57–61. | DOI

[23] H. Missbauer, W. Hauber and W. Stadler, A scheduling system for the steelmaking-continuous casting process. A case study from the steel-making industry. Int. J. Prod. Res. 47 (2009) 4147–4172. | DOI | Zbl

[24] B. Naderi, M. Zandieh, A.K.G. Balagh and V. Roshanaei, An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert Syst. Appl. 36 (2009) 9625–9633. | DOI

[25] T. Nishi, Y. Hiranaka and M. Inuiguchi, Lagrangian relaxation with cut generation for hybrid flow shop scheduling problems to minimize the total weighted tardiness. Comput. Oper. Res. 37 (2010) 189–198. | DOI | MR | Zbl

[26] D. Pacciarelli and M. Pranzo, Production scheduling in a steelmaking-continuous casting plant. Comput. Chem. Eng. 28 (2004) 2823–2835. | DOI

[27] Q.K. Pan, An effective co-evolutionary artificial bee colony algorithm for steelmaking-continuous casting scheduling. Eur. J. Oper. Res. 250 (2016) 702–714. | DOI | MR | Zbl

[28] Q.K. Pan, L. Wang, K. Mao, J.H. Zhao and M. Zhang, An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. IEEE Trans. Autom. Sci. Eng. 10 (2013) 307–322. | DOI

[29] C. Rajendran and D. Chaudhuri, A multi-stage parallel processor flowshop problem with minimum flowtime. Eur. J. Oper. Res. 57 (1992) 111–122. | DOI | Zbl

[30] R. Ruiz and C. Maroto, A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. Eur. J. Oper. Res. 169 (2006) 781–800. | DOI | MR | Zbl

[31] A. Sbihi, A. Bellabdaoui and J. Teghem, Solving a mixed integer linear program with times setup for the steel-continuous casting planning and scheduling problem. Int. J. Prod. Res. 52 (2014) 7276–7296. | DOI

[32] H. Sherali, S. Sarin and M. Kodialam, Models and algorithms for a two-stage production process. Prod. Plan. Control 1 (1990) 27–39. | DOI

[33] D.F. Shiau, S.C. Cheng and Y.M. Huang, Proportionate flexible flow shop scheduling via a hybrid constructive genetic algorithm. Expert Syst. Appl. 34 (2008) 1133–1143. | DOI

[34] L. Tang, and G. Wang, Decision Support system for the batching problems of steelmaking and continuous-casting production. Omega Int. J. Manag. Sci. 36 (2008) 976–991. | DOI

[35] L. Tang, J. Liu, A. Rong and Z. Yang, A mathematical programming model for scheduling steelmaking-continuous casting production. Eur. J. Oper. Res. 120 (2000) 423–435. | DOI | Zbl

[36] L. Tang, J. Liu, A. Rong and Z. Yang, A review of planning and scheduling systems and methods for integrated steel production. Eur. J. Oper. Res. 133 (2001) 1–20. | DOI | Zbl

[37] L. Tang, P.B. Luh, J. Liu and L. Fang, Steel-making process scheduling using Lagrangian relaxation. Int. J. Prod. Res. 40 (2002) 55–70. | DOI | Zbl

[38] L. Tang, H. Xuan and J. Liu, A new lagrangian relaxation algorithm for hybrid flow shop scheduling to minimize total weighted completion time. Comput. Oper. Res. 33 (2006) 3344–3359. | DOI | Zbl

[39] L. Tang, X. Wang and J. Liu, Color-coating production scheduling for coils in inventory in steel industry. Autom. Sci. Eng. IEEE Trans. 5 (2008) 544–549. | DOI

[40] W.S. Um, Computer simulation of the steelmaking process with ARENA. J. Korean Soc. Maint. Eng. 7 (2002) 77–90.

[41] H. Xuan and L. Tang, Scheduling a hybrid flow shop with batch production at the last stage. Comput. Oper. Res. 34 (2007) 2178–2733. | DOI | Zbl

[42] J. Yang, H. Che, F.P. Dou and T. Zhou, Genetic algorithm-based optimization used in rolling schedule. J. Iron Steel Res. Int. 5 (2008) 18–22. | DOI

[43] V. Yaurima, L. Burtseva and A. Tchernykh, Hybrid flowshop with unrelated machines, sequence dependent setup time, availability constraints and limited buffers. Comput. Ind. Eng. 56 (2009) 1452–1463. | DOI

[44] D.F. Zhu, Z. Zheng and X.Q. Gao, Intelligent optimization-based production planning and simulation analysis for steelmaking and continuous casting process. J. Iron Steel Res. Int. 17 (2010) 19–24. | DOI

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