Semi-Infinite Generalized Disjunctive and Mixed Integer Convex Programs with(out) Uncertainty

  • Manish Bansal
    • Categories 0-1 Programming, Convex Optimization, Semi-infinite Programming

    In this paper, we introduce semi-infinite generalized disjunctive programs that are defined by logical propositions along with disjunctions of sets of logical equations and infinite number of algebraic inequalities. We denote these programs by SIGDPs. For SIGDPs with linear and convex inequalities, we present new reformulations: semi-infinite mixed-binary/disjunctive linear programs and semi-infinite mixed-binary/disjunctive convex programs, … Read more

    Recognizing Series-Parallel Matrices in Linear Time

  • Matthias Walter
    • Categories Graphs and Matroids Tags ,

    A series-parallel matrix is a binary matrix that can be obtained from an empty matrix by successively adjoining rows or columns that are copies of an existing row/column or have at most one 1-entry. Equivalently, series-parallel matrices are representation matrices of graphic matroids of series-parallel graphs, which can be recognized in linear time. We propose … Read more

    ALSO-X#: Better Convex Approximations for Distributionally Robust Chance Constrained Programs

  • Nan Jiang
  • Weijun Xie
    • Categories Stochastic Programming Tags , , ,

    This paper studies distributionally robust chance constrained programs (DRCCPs), where the uncertain constraints must be satisfied with at least a probability of a prespecified threshold for all probability distributions from the Wasserstein ambiguity set. As DRCCPs are often nonconvex and challenging to solve optimally, researchers have been developing various convex inner approximations. Recently, ALSO-X has … Read more

    Fair and Risk-averse Urban Air Mobility Resource Allocation Under Uncertainties

  • Luying Sun
  • Weijun Xie
    • Categories Applications - OR and Management Sciences Tags , , , ,

    Urban Air Mobility (UAM) is an emerging air transportation mode to alleviate the ground traffic burden and achieve zero direct aviation emissions. Due to the potential economic scaling effects, the UAM traffic flow is expected to increase dramatically once implemented, and its market can be substantially large. To be prepared for the era of UAM, … Read more

    Recovering Dantzig-Wolfe Bounds by Cutting Planes

  • Rui Chen
  • Oktay Gunluk
  • Andrea Lodi
    • Categories (Mixed) Integer Linear Programming, Cutting Plane Approaches Tags , ,

    Dantzig-Wolfe (DW) decomposition is a well-known technique in mixed-integer programming (MIP) for decomposing and convexifying constraints to obtain potentially strong dual bounds. We investigate cutting planes that can be derived using the DW decomposition algorithm and show that these cuts can provide the same dual bounds as DW decomposition. More precisely, we generate one cut … Read more

    On an iteratively reweighted linesearch based algorithm for nonconvex composite optimization

  • Silvia Bonettini
  • Marco Prato
  • Simone Rebegoldi
    • Categories Nonlinear Optimization, Nonsmooth Optimization Tags , ,

    In this paper we propose a new algorithm for solving a class of nonsmooth nonconvex problems, which is obtained by combining the iteratively reweighted scheme with a finite number of forward–backward iterations based on a linesearch procedure. The new method overcomes some limitations of linesearch forward–backward methods, since it can be applied also to minimize … Read more

    A Novel Stepsize for Gradient Descent Method

  • Pham Thi Hoai
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Nonlinear Optimization Tags , , , ,

    In this paper, we propose a novel stepsize for the classical gradient descent scheme to solve unconstrained nonlinear optimization problems. We are concerned with the convex and smooth objective without the globally Lipschitz gradient condition. Our new method just needs the locally Lipschitz gradient but still gets the rate $O(\frac{1}{k})$ of $f(x^k)-f_*$ at most. By … Read more

    Prescriptive price optimization using optimal regression trees

  • Shunnosuke Ikeda
  • Naoki Nishimura
  • Noriyoshi Sukegawa
  • Yuichi Takano
    • Categories (Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Marketing Tags , ,

    This paper focuses on prescriptive price optimization, which derives the optimal pricing strategy that maximizes future revenue or profit by using demand forecasting models for multiple products. Prescriptive price optimization requires accurate demand forecasting models because the accuracy of these models has a direct impact on pricing strategies aimed at increasing revenue or profit. However, … Read more

    Efficient Discovery of Cost-effective Policies in Sequential, Medical Decision-Making Problems

  • Narges Mohammadi
  • M Skandari
    • Categories Applications - OR and Management Sciences, Dynamic Programming Tags , , ,

    Cost-effectiveness analysis (CEA) is extensively employed by healthcare policymakers to guide funding decisions and inform optimal design of medical interventions. In the CEA literature, willingness to pay (WTP) serves as a common metric for converting health benefits into monetary value and defining the net monetary benefit of an intervention. However, there is no universally accepted … Read more