The probabilistic set-covering problem

Operations Research

Volumn 50, Issue 6, 2002, Pages

  Beraldi, Patrizia ^a   Ruszczyński, Andrzej ^b  

^a UNIVERSITY OF CALABRIA   (Italy)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; PROBABILITY; PROBLEM SOLVING; SET THEORY; THEOREM PROVING;

SET-COVERING PROBLEM;

CONSTRAINT THEORY;

EID: 0036878896     PISSN: 0030364X     EISSN: None     Source Type: Journal    
DOI: 10.1287/opre.50.6.956.345     Document Type: Article

References (29)

1. Balas, E. 1983. A class of location, distribution and scheduling problems: Modeling and solution methods. P. Gray, L. Yuanzhang, eds. Proc. Chinese-U.S. Symposium on System Analysis. J. Wiley and Sons, New York.
2. _, M. C. Carrera. 1996. A dynamic subgradient-based branch-and-bound procedure for set covering. Oper. Res. 44 875-890.
3. Beasley, J. E. 1987. An algorithm for set covering problems. Eur. J. Oper. Res. 31 85-93.
4. _. 1990a. A Lagrangian heuristic for set covering problems. Naval Res. Logist. 37 151-164.
5. _. 1990b. OR-library: Distributing test problems by electronic mail. J. Oper. Res. Soc. 41 1069-1072.
6. _, P. C. Chu. 1996. A genetic algorithm for the set covering problem. Eur. J. Oper. Res. 94 392-404.
7. _, K. Jørnsten. 1992. Enhancing an algorithm for set covering problems. Eur. J. Oper. Res. 58 293-300.
8. Becker, T., V. Weispfenning. 1993. Gröbner Bases. Springer-Verlag, New York.
9. Beraldi, P. 1999. Programmazione stocastica intera sotto vincoli probabilistici. Ph.D. thesis, University of Calabria, Rende, Italy.
10. _, A. Ruszczyński. 2001. The probabilistic set covering problem. Rutcor Research Report 32-2001, Rutgers University, Piscataway, NJ.
11. Birge, J. R., F. Louveaux. 1997. Introduction to Stochastic Programming. Springer-Verlag, New York.
12. Borndörfer, R. 1998. Aspects of set packing, partitioning and covering. Shaker Verlag, Aachen, Germany.
13. Caprara, A., M. Fischetti, P. Toth. 1999. A heuristic method for the set covering problem. Oper. Res. 47 730-743.
14. _, _, _. 2000. Algorithms for the set covering problem. Ann. Oper. Res. 98 353-371.
15. Ceria, S., P. Nobili, A. Sassano. 1998a. A Lagrangian-based heuristic for large-scale set covering problems. Math. Programming 81 215-228.
16. _, _, _. 1998b. Set covering problem. M. Dell'Amico, F. Maffioli, A. Sassano, eds. Annotated Bibliographies in Combinatorial Optimization. John Wiley and Sons, New York, 415-428.
17. Chvátal, V. 1979. A greedy heuristic for the set covering problem. Math. Oper. Res. 4 233-235.
18. CPLEX Optimization, Inc. 1999. ILOG CPLEX 6.5: User's Manual. CPLEX Optimization, Inc., Incline Village, NV.
19. Dentcheva, D., A. Prékopa, A. Ruszczyński. 2000. Concavity and efficient points of discrete distributions in probabilistic programming. Math. Programming 89 55-77.
20. Gendreau, M., G. Laporte, R. Séguin. 1996. Stochastic vehicle routing. Eur. J. Oper. Res. 88 3-12.
21. Haddadi, S. 1997. Simple Lagrangian heuristic for the set covering problem. Eur. J. Oper. Res. 97 200-204.
22. Jacobs, L. W., M. J. Brusco. 1995. A local search heuristic for large set covering problems. Naval Res. Logist. 52 1129-1140.
23. Laporte, G., F. V. Louveaux, H. Mercure. 1989. Models and exact solutions for a class of stochastic location-routing problems. Eur. J. Oper. Res. 39 71-78.
24. Lorena, L. A. N., F. B. Lopes. 1994. A surrogate heuristic for set covering problems. Eur. J. Oper. Res. 79 138-150.
25. Nobili, P., A. Sassano. 1992. A separation routine for set covering polytope. E. Balas, G. Cornuejols, R. Kannan, eds. Integer Programming and Combinatorial Optimization. Carnegie Mellon University Press, Pittsburgh, PA.
26. Prékopa, A. 1990. Dual method for the solution of one-stage stochastic programming problem with random RHS obeying a discrete probability distribution. Z. Oper. Res. Methods Models Oper. Res. 34 441-461.
27. _, 1995. Stochastic Programming. Kluwer, Boston, MA.
28. Prékopa A., B. Vizvári, T. Badics, 1998. Programming under probabilistic constraint with discrete random variable. F. Giannesi, S. Komlósi, T. Rapcsák, eds. New Trends in Mathematical Programming. Kluwer, Boston, MA, 235-255.
29. Sen, S. 1992. Relaxations for the probabilistically constrained programs with discrete random variables. Oper. Res. Lett. 11 81-86.