A model-based rescheduling framework for managing abnormal supply chain events

Computers and Chemical Engineering

Volumn 31, Issue 5-6, 2007, Pages 496-518

  Adhitya, Arief ^a   Srinivasan, Rajagopalan ^a   Karimi, I A ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Crude oil; Optimization; Reactive scheduling; Risk management; Uncertainty

Indexed keywords

CRUDE PETROLEUM; DECISION SUPPORT SYSTEMS; GRAPH THEORY; HEURISTIC METHODS; MATHEMATICAL MODELS; RISK MANAGEMENT;

COMPOSITE OPERATIONS GRAPH; REACTIVE SCHEDULING; SUPPLY CHAIN OPERATIONS;

INDUSTRIAL MANAGEMENT;

CRUDE PETROLEUM; DECISION SUPPORT SYSTEMS; GRAPH THEORY; HEURISTIC METHODS; INDUSTRIAL MANAGEMENT; MATHEMATICAL MODELS; RISK MANAGEMENT;

EID: 33847099674     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2006.07.002     Document Type: Article

References (32)

1. Abumaizar R.J., and Svestka J.A. Rescheduling job shops under random disruptions. International Journal of Production Research 35 (1997) 2065-2082
2. Adhitya, A., Srinivasan, R., & Karimi, I. A. (2006). Managing abnormal events in refinery supply chains by heuristic rescheduling. Technical report. Laboratory for Intelligent Applications in Chemical Engineering, National University of Singapore.
3. Akturk M.S., and Gorgulu E. Theory and methodology-Match-up scheduling under a machine breakdown. European Journal on Operational Research 112 (1999) 81-97
4. Aytug H., Lawley M.A., McKay K., Mohan S., and Uzsoy R. Executing production schedules in the face of uncertainties: A review and some future directions. European Journal on Operational Research 161 1 (2005) 86-110
5. Belz R., and Mertens P. Combining knowledge-based systems and simulation to solve rescheduling problems. Decision Support System 17 (1996) 141-157
6. Bussmann S., Jennings N.R., and Wooldridge M. MultiAgent systems for manufacturing control: A design methodology (2004), Springer, Berlin
7. Filar J.A., Manyem P., and White K. How airlines and airports recover from schedule perturbations: A survey. Annals of Operations Research 108 (2001) 315-333
8. Henseler, H. (1994). Reaktion: A system for event independent reactive scheduling. In Artificial intelligence in reactive scheduling (pp. 19-31). UK: Chapman and Hall.
9. Herroelen W., and Leus R. Robust and reactive project scheduling: A review and classification of procedures. International Journal of Production Research 42 8 (2004) 1599-1620
10. Jo G.-S., Jung J.-J., Koo J.-H., and Hyun S.-H. Ramp activity expert system for scheduling and coordination at an airport. AI Magazine Winter (2000) 75-82
11. Julka N., Srinivasan R., and Karimi I.A. Agent-based supply chain management-1: Framework. Computers and Chemical Engineering 26 12 (2002) 1755-1769
12. Julka N., Srinivasan R., and Karimi I.A. Agent-based supply chain management-2: A refinery application. Computers and Chemical Engineering 26 12 (2002) 1771-1781
13. Kelley J.D., and Mann J.L. Crude-oil blend scheduling optimization: An application with multi-million dollar benefits-Part 1. Hydrocarbon Processing 82 6 (2003) 47-54
14. Kunnathur A.S., Sundararaghavan P.S., and Sampath S. Dynamic rescheduling using a simulation-based expert system. Journal of Manufacturing Technology Management 15 (2004) 199-212
15. Li H., Li Z., Li L.X., and Hu B. A production rescheduling expert simulation system. European Journal on Operational Research 124 (2000) 283-293
16. Mathaisel D.F.X. Decision support for airline system operations control and irregular operations. Computers and Operations Research 23 11 (1996) 1083-1098
17. Mishra M., Srinivasan R., and Karimi I.A. Managing disruptions in refinery supply chain using an agent-based decision support system. Presented in the AIChE annual meeting. San Francisco, November 16-21 (2003)
18. Mishra M., Srinivasan R., and Karimi I.A. A model-based framework for detecting, diagnosing, and rectifying supply chain disruptions. Presented in the AIChE annual meeting. Austin, TX, November 7-12 (2004)
19. Rangsaritratsamee R., Ferrell Jr. W.G., and Kurz M.B. Dynamic rescheduling that simultaneously considers efficiency and stability. Computers and Industrial Engineering 46 (2004) 1-15
20. Reddy C.P., Karimi I.A., and Srinivasan R. A new continuous-time formulation for scheduling crude oil operations. Chemical Engineering Science 59 6 (2004) 1325-1341
21. Reddy C.P., Karimi I.A., and Srinivasan R. Novel solution approach for optimizing crude oil operations. AIChE Journal 50 6 (2004) 1177-1197
22. Rosenberger J.M., Johnson E.L., and Nemhauser G.L. Rerouting aircraft for airline recovery. Transportation Science 37 4 (2003) 408-421
23. Roslöf J., Harjunkoski I., Björkqvist J., Karlsson S., and Westerlund T. An MILP-based reordering algorithm for complex industrial scheduling and rescheduling. Computers and Chemical Engineering 25 (2001) 821-828
24. Russell S.J., and Norvig P. Artificial intelligence: A modern approach (2003), Prentice Hall, Upper Saddle River
25. Sheffi Y. The resilient enterprise: Overcoming vulnerability for competitive advantage (2005), MIT Press, Cambridge
26. Sheffi Y., Rice Jr. J.B., Fleck J.M., and Caniato F. Supply chain response to global terrorism: A situation scan. European OMA-POMS conference (2003)
27. Singapore Refining Company (2003). Personal communication.
28. Subramaniam V., and Raheja A.S. mAOR: A heuristic-based reactive repair mechanism for job shop schedules. International Journal of Advanced Manufacturing Technology 22 (2003) 669-680
29. Vin J.P., and Ierapetritou M.G. A new approach for efficient rescheduling of multiproduct batch plants. Industrial Engineering and Chemistry Research 39 (2000) 4228-4238
30. Wilson M.C. Transportation disruptions in the supply chain: Simulator as a decision support tool. Proceedings of the 31st annual logistics educators conference (2002)
31. Wooldridge M. An introduction to multiagent systems (2002), John Wiley & Sons, Chichester
32. Yu G., and Xi Q. Disruption management: Framework, models and applications (2004), World Scientific Publishing Company, Singapore