Generation of Deep Cuts Using the Fundamental Disjunctive Inequality

Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 181)


Recall from Chapter I that our motivation in using disjunctive programming methods is to aid us in solving nonconvex problems of the type
$$\begin{gathered} DP: minimize (fx) \hfill \\ subject to x\varepsilon X \hfill \\ \end{gathered}$$
$$\begin{gathered} x \varepsilon U S_h \hfill \\ h\varepsilon H \hfill \\ \end{gathered}$$
where f: Rn → R is lower semicontinuous, X is a closed subset of the nonnegative orthant of Rn and each Sh, h ε H is given by Equation (1.1).


Intuitive Appeal Nonnegative Orthant Subgradient Optimization Surrogate Constraint Rectilinear Distance 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1980

Authors and Affiliations

  1. 1.School of Industrial Engineering and Operations ResearchVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  2. 2.School of Industrial and Systems EngineeringGeorgia Institute of TechnologyAtlantaUSA

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