Reformulation-Linearization Techniques for Discrete Optimization Problems

  • Hanif D. Sherali
  • Warren P. Adams


Discrete and continuous nonconvex programming problems arise in a host of practical applications in the context of production, location-allocation, distribution, economics and game theory, process design, and engineering design situations. Several recent advances have been made in the development of branch-and-cut algorithms for discrete optimization problems and in polyhedral outer-approximation methods for continuous nonconvex programming problems. At the heart of these approaches is a sequence of linear programming problems that drive the solution process. The success of such algorithms is strongly tied in with the strength or tightness of the linear programming representations employed.


Convex Hull Discrete Optimization Valid Inequality Quadratic Assignment Problem Discrete Optimization Problem 
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Copyright information

© Kluwer Academic Publishers 1998

Authors and Affiliations

  • Hanif D. Sherali
    • 1
  • Warren P. Adams
    • 2
  1. 1.Department of Industrial and Systems EngineeringVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  2. 2.Department of Math SciencesClemson UniversityClemsonUSA

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