- AHUJA, R. K., MAGNATI, T. L., AND ORLIN, J. B. 1993. Network Flows: Theory, Algorithms and Applications. Prentice-Hall, Englewood Cliffs, NJ. Google Scholar
- CONFORTI, M., CORNUEJOLS, G., KAPOOR, A., VUSK- OVIC, K., AND RAO, M. R. 1994. Balanced matrices. In Mathematical Programming, State of the Art 1994, J. R. Binge and K. G. Murty, Eds., University of Michigan.Google Scholar
- COOK, W., LOVASZ, L., AND SEYMOUR, P., ED. 1995. Combinatorial Optimization: Papers from the DIMACS Special Year, Series in Discrete Mathematics and Theoretical Computer Science, Vol. 20. AMS, Providence, RI.Google Scholar
- FOURER, R., GAY, D. M., AND KERNIGHIAN, B. W. 1993. AMPL: A Modeling Language for Mathematical Programming. Scientific Press.Google Scholar
- GROTSCHEL, M., LOVASZ, L., AND SCHRIJVER, A. 1988. Geometric Algorithms and Combinatorial Optimization. Springer-Verlag, New York.Google Scholar
- LUSTIG, I. J., MARSTEN, R. E., AND SHANNO, D. F. 1994. Interior point methods for linear programming: Computational state of the art. ORSA J. Comput. 6, 1, 1-14.Google Scholar
- NEMHAUSER, G. L. AND WOLSEY, L. A. 1988. Integer and Combinatorial Optimization. Wiley, New York. Google Scholar
- PADBERG, M.W. 1995. Linear Optimization and Extensions. Springer-Verlag, New York.Google Scholar
- PULLEYBLANK, W.R. 1989. Polyhedral combinatonics. In Handbooks in Operations Research and Management Science (Vol. 1: Optimization). G. L. Nemhauser, A. H. G. Rinooy Kan, and M. J. Todd, Eds. North Holland, Amsterdam, 371-446. Google Scholar
- SARASWAT, V. AND VAN HENTENRYCK, P., EDS. 1995. Principles and Practice of Constraint Programming. MIT Press, Cambridge, MA.Google Scholar
Index Terms
- Combinatorial optimization: an integer programming perspective
Recommendations
Quadratic Combinatorial Optimization Using Separable Underestimators
Binary programs with a quadratic objective function are NP-hard in general, even if the linear optimization problem over the same feasible set is tractable. In this paper, we address such problems by computing quadratic global underestimators of the ...
On Interior-Point Warmstarts for Linear and Combinatorial Optimization
Despite the many advantages of interior-point algorithms over active-set methods for linear optimization, one of the remaining practical challenges is their current limitation to efficiently solve series of related problems by an effective warmstarting ...
Comments