A two-stage scheduling method for hot rolling and its application

Control Engineering Practice

Volumn 17, Issue 6, 2009, Pages 629-641

  Zhao, Jun ^a   Wang, Wei ^a   Liu, Quanli ^a   Wang, Zhigang ^a   Shi, Peng ^b  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^b UNIVERSITY OF GLAMORGAN   (United Kingdom)

Author keywords

Heuristics; Hot rolling production scheduling; Intelligent search algorithms; Vehicle routing problem with time windows

Indexed keywords

BAOSTEEL; ECONOMIC BENEFITS; HEURISTICS; HOT CHARGES; HOT STRIP MILLS; INTELLIGENT SEARCH ALGORITHMS; PRODUCTION EFFICIENCIES; ROLLING SCHEDULING; SCHEDULING METHODS; STEEL PROCESSING; TWO STAGES; VEHICLE ROUTING PROBLEM WITH TIME WINDOWS;

HEURISTIC METHODS; HOT ROLLING MILLS; LEARNING ALGORITHMS; METAL WORKING; PRODUCTION ENGINEERING; ROUTING ALGORITHMS; SCHEDULING; STRIP MILLS; VEHICLE ROUTING; WINDOWS;

HOT ROLLING;

EID: 64249089382     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2008.10.014     Document Type: Article

References (16)

1. Assaf I., Chen M., and Katzberg J. Steel production schedule generation. International Journal of Production Research 35 2 (1997) 467-477
2. Baker A.B. Intelligent backtracking on the hardest constraint problems. Journal of Artificial Intelligent Research (1995)
3. Cowling P. A flexible decision support system for steel hot rolling mill scheduling. Computers and Industrial Engineering 45 2 (2003) 307-321
4. Desrochers M., Desrosiers J., and Solomon M. A new optimization algorithm for the vehicle routing problem with time windows. Operations Research 40 2 (1992) 342-354
5. Homberger J., and Gehring H. Two evolutionary metaheuristics for the vehicle routing problem with time windows. INFOR Journal 37 3 (1999) 297-318
6. Katayama, K., & Narihisa, H. (2001). On fundamental design of parthenogenetic algorithm for the binary quadratic programming problem. In: Proceedings of the congress on evolutionary computation, Seoul.
7. Kelleher G., and Cavichiollo P. Supporting rescheduling using CSP, RMS and POB-An example application. Journal of Intelligent Manufacturing 12 4 (2001) 343-357
8. Kosiba E.D., Wright J.R., and Cobbs A.E. Discrete event sequencing as a traveling salesman problem. Computers in Industry 19 3 (1992) 317-327
9. Lopez L., Carter M.W., and Gendreau M. The hot strip mill production scheduling problem: A tabu search approach. European Journal of Operational Research 106 2-3 (1998) 317-335
10. Minton S., Johnston M.D., Philips A.B., and Laird P. Minimizing conflicts: A heuristic repair method for constraint-satisfaction and scheduling problems. Artificial Intelligence 58 1 (1992) 161-205
11. Peterson C.M., Sorensen K.L., and Vidal R.V.V. Inter-process synchronization in steel production. International Journal of Production Research 30 1 (1992) 1415-1425
12. Savelsbergh M.W.P. Local search in routing problems with time windows. Annals of Operations Research 33 4 (1985) 285-305
13. Shin D., Kim J., Choo J., and Singh C. Optimal service restoration and reconfiguration of network using genetic-tabu algorithm. Electric Power Systems Research 71 2 (2004) 145-152
14. Srinivas M., and Patnaik L.M. Adaptive probabilities of crossover and mutation in genetic algorithms. IEEE Transactions on System, Man and Cybernetics 24 4 (1994) 656-667
15. Tang L., Liu J., Rong A., and Yang Z. A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex. European Journal of Operational Research 124 2 (2000) 267-282
16. Tang L., Luh P.B., Liu J., and Fang L. Steel-making process scheduling using Lagrangian relaxation. International Journal of Production Research 40 1 (2002) 55-70