A branch-and-price-and-cut method for ship scheduling with limited risk

Transportation Science

Volumn 42, Issue 3, 2008, Pages 336-351

  Hwang, Hee Su ^a   Visoldilokpun, Siriwat ^b   Rosenberger, M Jay ^b  

^a US Airways   (United States)

^b The University of Texas at Arlington   (United States)

Author keywords

Branch and cut and price; Convex programming; Quadratic constraint; Risk reduction; Ship scheduling

Indexed keywords

CONVEX OPTIMIZATION; COSTS; SCHEDULING; SHIPS;

BRANCH AND CUT AND PRICES; BRANCH-AND-PRICE-AND-CUT; COMPUTATIONAL RESULTS; CUTTING PLANE ALGORITHMS; QUADRATIC CONSTRAINT; RISK REDUCTIONS; SHIP SCHEDULING; VARIANCE CONSTRAINTS;

INTEGER PROGRAMMING;

EID: 70449644836     PISSN: 00411655     EISSN: 15265447     Source Type: Journal    
DOI: 10.1287/trsc.1070.0218     Document Type: Article

References (36)

1. Andersson, T., P. Värbrand. 2004. The flight perturbation problem. Transportation Planning Tech. 27(2)91-117.
2. Appelgren, L. H. 1969. A column generation algorithm for a ship scheduling problem. Transportation Sci. 3(1)53-68.
3. Appelgren, L. H. 1971. Integer programming methods for a vessel scheduling problem. Transportation Sci. 5(1)64-78.
4. Azaron, A., F. Kianfar. 2003. Dynamic shortest path in stochastic dynamic networks: Ship routing problem. Eur. J. Oper. Res. 144(1)138-156.
5. Bremer, W. M., A. N. Perakis. 1992. An operational tanker scheduling optimization system: Model implementation, results and possible extensions. Maritime Policy Management 19(3)189-199.
6. Brown, G. G., G. W. Graves, D. Ronen. 1987. Scheduling ocean transportation of crude oil. Management Sci. 33(3)335-446.
7. Canovas, L., M. Landete, A. Marin. 2002. On the facets of the simple plant location packing polytope. Discrete Appl. Math. 124 27-54.
8. Chajakis, E. D. 1997. Sophisticated crude transportation. OR/MS Today 24(6)30-34.
9. Chajakis, M. 1999. Reflections on a marine vessel affair: A management science sea story. OR/MS Today 26(4)32-37.
10. Cheng, L., M. A. Duran. 2004. Logistics for world-wide crude oil transportation using discrete event simulation and optimal control. Comput. Chemical Engrg. 28(6-7)897-911.
11. Cho, D. C., E. L. Johnson, M. Padberg, M. R. Rao. 1983. On the uncapacitated plant location problem I: Valid inequalities and facets. Math. Oper. Res. 8(4)579-589. (Pubitemid 14490614)
12. Christiansen, M., K. Fagerholt, D. Ronen. 2004. Ship routing and scheduling: Status and perspectives. Transportation Sci. 38(1)1-18.
13. COIN-OR. 2005. The computational infrastructure for operations research. http://www.coin-or.org/.
14. Dantzig, G. B., D. R. Fulkerson. 1954. Minimizing the number of tankers to meet a fixed schedule. Naval Res. Logist. Quart. 1 217-222.
15. Desaulniers, G., A. Langevin, D. Riopel, B. Villeneuve. 2003. Dispatching and conflict-free routing of automated guided vehicles: An exact approach. Internat. J. Flexible Manufacturing Systems 15(4)309-331.
16. Gosselin, P. G. 2004. THE NEW DEAL: How just a handful of setbacks sent the Ryans tumbling out of prosperity. Los Angeles Times (December 30) A1.
17. Kelley, J. E. 1960. The cutting-plane method for solving convex programs. SIAM J. Appl. Math. 8 703-712.
18. Kim, S.-H., K. Lee. 1997. An optimization-based decision support system for ship scheduling. Comput. Indust. Engrg. 33(3-4)689-692.
19. Klabjan, D., E. L. Johnson, G. L. Nemhauser, E. Gelman, S. Ramaswamy. 2001. Solving large airline crew scheduling problems: Random pairing generation and strong branching. Computational Optim. Appl. 20 (1, October)73-91.
20. Kong, N. 2005. The optimal design of regions for organ transplantation. Unpublished doctoral dissertation, University of Pittsburgh, Pittsburgh.
21. Lo, H. K., M. R. McCord. 1998. Adaptive ship routing through stochastic ocean currents: General formulations and empirical results. Transportation Res., Part A: Policy Practice 32(7)547-561.
22. Mehrotra, A., E. L. Johnson, G. L. Nemhauser. 1998. An optimization based heuristic for political districting. Management Sci. 44(8)1100-1114.
23. Moore, E. H. 1920. On the reciprocal of the general algebraic matrix. Bull. Amer. Math. Soc. 26 394-395.
24. OPEC. 2005. Organization of the Petroleum Exporting Countries. http://www.opec.org/.
25. Penrose, R. 1955. A generalized inverse for matrices. Proc. Cambridge Philos. Soc. 51 406-413.
26. Perakis, A. N., W. M. Bremer. 1992. An operational tanker scheduling optimization system: Background, current practice and model formulation. Maritime Policy Management 19(3)177-187.
27. Ronen, D. 1983. Cargo ships routing and scheduling: Survey of models and problems. Eur. J. Oper. Res. 12 119-126.
28. Ronen, D. 1993. Ship scheduling: The last decade. Eur. J. Oper. Res. 71 325-333.
29. Rosenberger, J. M., E. L. Johnson, G. L. Nemhauser. 2003. Rerouting aircraft for airline recovery. Transportation Sci. 37(4)408-421.
30. Rossi, F., S. Smriglio. 2001. A set packing model for the ground holding problem in congested networks. Eur. J. Oper. Res. 131(4)400-416.
31. Ryan, D. M., B. A. Foster. 1981. An integer programming approach to scheduling. A. Wren, ed. Computer Scheduling of Public Transport Urban Passenger Vehicle and Crew Scheduling. North-Holland, Amsterdam, 269-280.
32. Sharpe, W. F. 1970. Portfolio Theory and Capital Markets. McGraw-Hill, New York.
33. Sindhuchao, S., H. E. Romeijn, E. Akçali, R. Boondiskulchok. 2005. An integrated inventory-routing system for multi-item joint replenishment with limited vehicle capacity. J. Global Optim. 32(1)93-118.
34. Vance, P. H., A. Atamturk, C. Barnhart, E. Gelman, E. L. Johnson, A. Krishna, D. Madidhara, G. L. Nemhauser, R. Rebello. 1997. A heuristic branch-and-price approach for the airline crew pairing problem. Technical Report TLI/LEC-97-06, Georgia Institute of Technology, Atlanta.
35. Worldscale. 2000. New worldwide tanker nominal freight scale. http://www.worldscale.co.uk/Worldscale/.
36. Wu, D. O. 2002. Linear algebra. http://www.wu.ece.ufl.edu/books/math/ algebra/LinearAlgebra.html/