Now showing items 1-4 of 4

    • Effective Separation of Disjunctive Cuts for Convex Mixed Integer Nonlinear Programs 

      Kilinc, Mustafa; Linderoth, Jeff; Luedtke, James (University of Wisconsin-Madison Department of Computer Sciences, 2010)
      We describe a computationally effective method for generating disjunctive inequalities for convex mixed-integer nonlinear programs (MINLPs). The method relies on solving a sequence of cut-generating linear programs, ...
    • Locally Ideal Formulations for Piecewise Linear Functions with Indicator Variables 

      Linderoth, Jeff; Luedtke, James; Sridhar, Srikrishna (2013-04-29)
      In this paper, we consider mixed integer linear programming (MIP) formulations for piecewise linear functions (PLFs) that are evaluated when an indicator variable is turned on. We describe modifications to standard MIP ...
    • Some Results on the Strength of Relaxations of Multilinear Functions\ 

      Luedtke, James; Namazifar, Mahdi; Linderoth, Jeff (University of Wisconsin-Madison Department of Computer Sciences, 2010)
      We study approaches for obtaining convex relaxations of global optimization problems containing multilinear functions. Specifically, we compare the concave and convex envelopes of these functions with the relaxations ...
    • Valid Inequalities for the Pooling Problem with Binary Variables 

      D'Ambrosio, Claudio; Linderoth, Jeff; Luedtke, James (University of Wisconsin-Madison Department of Computer Sciences, 2010)
      The pooling problem consists of finding the optimal quantity of final products to obtain by blending different compositions of raw materials in pools. Bilinear terms are required to model the quality of products in the ...