Applications – OR and Management Sciences

Estimating Bounds for Quadratic Assignment Problems Associated with Hamming and Manhattan Distance Matrices based on Semidefinite Programming

  • Hans D Mittelmann
  • Jiming Peng
    • Categories Applications - OR and Management Sciences, Semi-definite Programming Tags , , ,

    Quadratic assignment problems (QAPs) with a Hamming distance matrix of a hypercube or a Manhattan distance matrix of rectangular grids arise frequently from communications and facility locations and are known to be among the hardest discrete optimization problems. In this paper we consider the issue of how to obtain lower bounds for those two classes … Read more

    SHOWCASE SCHEDULING AT FRED ASTAIRE EAST SIDE DANCE STUDIO

  • Miguel A. Lejeune
  • Nevena Yakova
    • Categories Applications - OR and Management Sciences, Scheduling

    The ballroom dancing showcases at Fred Astaire East Side Dance Studio in Manhattan are held at least twice a year and provide the students with an environment for socializing, practice, and improvement. The most important part of a showcase organization is the construction of the dance presentations timetable, and, with the number of participants increasing … Read more

    Value-at-Risk optimization using the difference of convex algorithm

  • David Wozabal
    • Categories Finance and Economics, Global Optimization Applications, Stochastic Programming Tags , ,

    Value-at-Risk (VaR) is an integral part of contemporary financial regulations. Therefore, the measurement of VaR and the design of VaR optimal portfolios are highly relevant problems for financial institutions. This paper treats a VaR constrained Markowitz style portfolio selection problem when the distribution of returns of the considered assets are given in the form of … Read more

    Iterative Estimation Maximization for Stochastic Linear Programs with Conditional Value-at-Risk Constraints

  • Pu Huang
  • Dharmashankar Subramanian
    • Categories Convex Optimization, Finance and Economics, Stochastic Programming Tags , ,

    We present a new algorithm, Iterative Estimation Maximization (IEM), for stochastic linear programs with Conditional Value-at-Risk constraints. IEM iteratively constructs a sequence of compact-sized linear optimization problems, and solves them sequentially to find the optimal solution. The problem size IEM solves in each iteration is unaffected by the size of random samples, which makes it … Read more

    On-line Service Scheduling

  • Bo Chen
  • Wenxun Xing
  • Zhenbo Wang
    • Categories Approximation Algorithms, Scheduling Tags , , ,

    This paper is concerned with a scheduling problem that occurs in service systems, where customers are classified as `ordinary’ and `special’. Ordinary customers can be served on any service facility, while special customers can be served only on the flexible service facilities. Customers arrive dynamically over time and their needs become known upon arrival. We … Read more

    Parallel Space Decomposition of the Mesh Adaptive Direct Search algorithm

  • Charles Audet
  • John E. Dennis, Jr.
  • Sébastien Le Digabel
    • Categories Applications - OR and Management Sciences, Nonsmooth Optimization, Parallel Algorithms Tags , , , ,

    This paper describes a parallel space decomposition PSD technique for the mesh adaptive direct search MADS algorithm. MADS extends a generalized pattern search for constrained nonsmooth optimization problems. The objective of the present work is to obtain good solutions to larger problems than the ones typically solved by MADS. The new method PSD-MADS is an … Read more

    OrthoMADS: A deterministic MADS instance with orthogonal directions

  • Mark A. Abramson
  • Charles Audet
  • John E. Dennis, Jr.
  • Sébastien Le Digabel
    • Categories Applications - OR and Management Sciences, Nonsmooth Optimization Tags , , , ,

    he purpose of this paper is to introduce a new way of choosing directions for the mesh adaptive direct search (Mads) class of algorithms. The advantages of this new OrthoMads instantiation of Mads are that the polling directions are chosen deterministically, ensuring that the results of a given run are repeatable, and that they are … Read more

    Exact and heuristic solutions of the global supply chain problem with transfer pricing

  • Pierre Hansen
  • Sébastien Le Digabel
  • Sylvain Perron
  • Nenad Mladenovic
    • Categories Applications - OR and Management Sciences, Nonlinear Optimization, Supply Chain Management Tags , , , , ,

    We examine the example of a multinational corporation that attempts to maximize its global after tax profits by determining the flow of goods, the transfer prices, and the transportation cost allocation between each of its subsidiaries. Vidal and Goetschalckx (2001) proposed a bilinear model of this problem and solved it by an Alternate heuristic. We … Read more

    Passenger Name Record Data Mining Based Cancellation Forecasting for Revenue Management

  • Dolores Romero Morales
  • Jingbo Wang
    • Categories Data-Mining, Yield Management Tags , , , ,

    Revenue management (RM) enhances the revenues of a company by means of demand-management decisions. An RM system must take into account the possibility that a booking may be canceled, or that a booked customer may fail to show up at the time of service (no-show). We review the Passenger Name Record data mining based cancellation … Read more

    Geometric Rounding: A Dependent Rounding Scheme for Allocation Problems

  • Dongdong Ge
  • Yinyu Ye
  • Shuzhong Zhang
  • Simai He
  • Zizhuo Wang
    • Categories Applications - OR and Management Sciences, Approximation Algorithms

    This paper presents a general technique to develop approximation algorithms for allocation problems with integral assignment constraints. The core of the method is a randomized dependent rounding scheme, called geometric rounding, which yields termwise rounding ratios (in expectation), while emphasizing the strong correlation between events. We further explore the intrinsic geometric structure and general theoretical … Read more