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A Hybrid Modeling for Continuous Casting Scheduling Problem | ||
| AUT Journal of Modeling and Simulation | ||
| مقاله 5، دوره 49، شماره 2، اسفند 2017، صفحه 173-180 اصل مقاله (4.55 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2017.11583.4946 | ||
| نویسندگان | ||
| M. H. Fazel Zarandi؛ F. Kashani Azad؛ A. H. Karimi Kashani | ||
| Dept. of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| چکیده | ||
| This paper deals with a multi-agent-based interval type-2 fuzzy (IT2F) expert system for scheduling steel continuous casting. Continuous caster scheduling is a complex and extensive process that needs expert staff. In this study, a distributed multi-agent-based structure is proposed as a solution. The agents used herein can cooperate with each other via various communication protocols. To facilitate such communication, an appropriate negotiation protocol (i.e., contract net protocol) is proposed. The due dates specified by expert staff are represented by IT2F membership functions (MFs). As a part of the objective functions, a simple procedure is proposed to calculate the total earliness and tardiness penalty when the due date’s MFs are IT2F. The proposed hybrid multi-agentbased system combines the multi-agent systems with type-2 fuzzy concepts which conforms to the real-world continuous casting problem. | ||
تازه های تحقیق | ||
[1] D. Ouelhadj, A multi-agent system for the integrated dynamic scheduling of steel production, University of Nottingham, 2003. [2] P.I. Cowling, D. Ouelhadj, S. Petrovic, Dynamic scheduling of steel casting and milling using multi-agents, Production Planning & Control, 15(2) (2004) 178-188. [3] Y. Li, J.-Q. Zheng, S.-L. Yang, Multi-agent-based fuzzy scheduling for shop floor, The International Journal of Advanced Manufacturing Technology, 49(5) (2010) 689-695. [4] M.F. Zarandi, P. Ahmadpour, Fuzzy agent-based expert system for steel making process, Expert systems with applications, 36(5) (2009) 9539-9547. [5] O. Castillo, P. Melin, J. Kacprzyk, W. Pedrycz, Type-2 fuzzy logic: theory and applications, in: Granular Computing, 2007. GRC 2007. IEEE International Conference on, IEEE, 2007, pp. 145-145. [6] N.N. Karnik, J.M. Mendel, Operations on type-2 fuzzy sets, Fuzzy sets and systems, 122(2) (2001) 327-348. [7] J.M. Mendel, R.B. John, Type-2 fuzzy sets made simple, IEEE Transactions on fuzzy systems, 10(2) (2002) 117-127. [8] M.F. Zarandi, R. Gamasaee, Type-2 fuzzy hybrid expert system for prediction of tardiness in scheduling of steel continuous casting process, Soft Computing, 16(8) (2012) 1287-1302. [9] Q. Liang, J.M. Mendel, Interval type-2 fuzzy logic systems: theory and design, IEEE Transactions on Fuzzy systems, 8(5) (2000) 535-550. [10] J. Dorn, W. Slany, A flow shop with compatibility constraints in a steelmaking plant, na, 1994. [11] J. Dorn, Iterative improvement methods for knowledge-based scheduling, AI communications, 8(1) (1995) 20-34. [12] F. Liu, J.M. Mendel, An interval approach to fuzzistics for interval type-2 fuzzy sets, in: Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International, IEEE, 2007, pp. 1-6. [13] B. Lally, L. Biegler, H. Henein, A model for sequencing a continuous casting operation to minimize costs, Mathematical Modelling of Materials Processing Operations, (1987) 1157-1172. [14] L. Tang, J. Liu, A. Rong, Z. Yang, A mathematical programming model for scheduling steelmaking-continuous casting production, European Journal of Operational Research, 120(2) (2000) 423-435. [15] S.Y. Chang, M.-R. Chang, Y. Hong, A lot grouping algorithm for a continuous slab caster in an integrated steel mill, Production planning & control, 11(4) (2000) 363-368. | ||
| کلیدواژه‌ها | ||
| Steel production؛ Continuous caster scheduling؛ Agent-based system؛ Negotiation؛ Fuzzy system | ||
| مراجع | ||
|
[1] D. Ouelhadj, A multi-agent system for the integrated dynamic scheduling of steel production, University of Nottingham, 2003.
[2] P.I. Cowling, D. Ouelhadj, S. Petrovic, Dynamic scheduling of steel casting and milling using multi-agents, Production Planning & Control, 15(2) (2004) 178-188.
[3] Y. Li, J.-Q. Zheng, S.-L. Yang, Multi-agent-based fuzzy scheduling for shop floor, The International Journal of Advanced Manufacturing Technology, 49(5) (2010) 689-695.
[4] M.F. Zarandi, P. Ahmadpour, Fuzzy agent-based expert system for steel making process, Expert systems with applications, 36(5) (2009) 9539-9547.
[5] O. Castillo, P. Melin, J. Kacprzyk, W. Pedrycz, Type-2 fuzzy logic: theory and applications, in: Granular Computing, 2007. GRC 2007. IEEE International Conference on, IEEE, 2007, pp. 145-145.
[6] N.N. Karnik, J.M. Mendel, Operations on type-2 fuzzy sets, Fuzzy sets and systems, 122(2) (2001) 327-348.
[7] J.M. Mendel, R.B. John, Type-2 fuzzy sets made simple, IEEE Transactions on fuzzy systems, 10(2) (2002) 117-127.
[8] M.F. Zarandi, R. Gamasaee, Type-2 fuzzy hybrid expert system for prediction of tardiness in scheduling of steel continuous casting process, Soft Computing, 16(8) (2012) 1287-1302.
[9] Q. Liang, J.M. Mendel, Interval type-2 fuzzy logic systems: theory and design, IEEE Transactions on Fuzzy systems, 8(5) (2000) 535-550.
[10] J. Dorn, W. Slany, A flow shop with compatibility constraints in a steelmaking plant, na, 1994.
[11] J. Dorn, Iterative improvement methods for knowledge-based scheduling, AI communications, 8(1) (1995) 20-34.
[12] F. Liu, J.M. Mendel, An interval approach to fuzzistics for interval type-2 fuzzy sets, in: Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International, IEEE, 2007, pp. 1-6.
[13] B. Lally, L. Biegler, H. Henein, A model for sequencing a continuous casting operation to minimize costs, Mathematical Modelling of Materials Processing Operations, (1987) 1157-1172.
[14] L. Tang, J. Liu, A. Rong, Z. Yang, A mathematical programming model for scheduling steelmaking-continuous casting production, European Journal of Operational Research, 120(2) (2000) 423-435.
[15] S.Y. Chang, M.-R. Chang, Y. Hong, A lot grouping algorithm for a continuous slab caster in an integrated steel mill, Production planning & control, 11(4) (2000) 363-368. | ||
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