Month: March 2019

Day-Ahead Contingency-Constrained Unit Commitment with Co-Optimized Post-Contingency Transmission Switching

  • José Manuel Arroyo
  • Raphael Saavedra
  • Alexandre Street
    • Categories Applications - OR and Management Sciences Tags , , ,

    Transmission switching has been previously shown to offer significant benefits to power system operation, such as cost savings and the reduction of power imbalance levels. Within the context of co-optimized electricity markets for energy and reserves, this paper addresses the incorporation of transmission switching in the contingency-constrained unit commitment problem. The proposed generation scheduling model … Read more

    A Method for Convex Black-Box Integer Global Optimization

  • Jeffrey Larson
  • Sven Leyffer
  • Prashant Palkar
  • Stefan M. Wild
    • Categories Convex Optimization Tags , , ,

    We study the problem of minimizing a convex function on the integer lattice when the function cannot be evaluated at noninteger points. We propose a new underestimator that does not require access to (sub)gradients of the objective but, rather, uses secant linear functions that interpolate the objective function at previously evaluated points. These linear mappings … Read more

    Efficient Derivative Evaluation for Rigid-body Dynamics based on Recursive Algorithms subject to Kinematic and Loop Constraints

  • Christian Kirches
  • Manuel Kudruss
  • Paul Manns
    • Categories Control Applications

    Simulation, optimization and control of robotic and bio-mechanical systems depend on a mathematical model description, typically a rigid-body system connected by joints, for which efficient algorithms to compute the forward or inverse dynamics exist. Models that e.g.\ include spring-damper systems are subject to both kinematic and loop constraints. Gradient-based optimization and control methods require derivatives … Read more

    CONICOPF: Conic relaxations for AC optimal power flow computations

  • Christian Bingane
  • Miguel F. Anjos
  • Sébastien Le Digabel
    • Categories Semi-definite Programming Tags , , ,

    Computational speed and global optimality are key needs for practical algorithms for the optimal power flow problem. Two convex relaxations offer a favorable trade-off between the standard second-order cone and the standard semidefinite relaxations for large-scale meshed networks in terms of optimality gap and computation time: the tight-and-cheap relaxation (TCR) and the quadratic convex relaxation … Read more

    An Iterative Graph Expansion Approach for the Scheduling and Routing of Airplanes

  • Armin Fügenschuh
  • Fabian Gnegel
    • Categories (Mixed) Integer Linear Programming, Branch and Cut Algorithms, Transportation Tags , , ,

    A tourism company that offers fly-in safaris is faced with the challenge to route and schedule its fleet of airplanes in an optimal way. Over the course of a given time horizon several groups of tourists have to be picked up at airports and flown to their destinations within a certain time-window. Furthermore the number … Read more

    Team as a Service: Team Formation on Social Networks

  • Nihal Berktas
  • Hande Yaman
    • Categories 0-1 Programming, Applications - OR and Management Sciences Tags , , , ,

    Team as a Service (TaaS) is a new outsourcing service that enables on-demand creation and management of distributed teams for fast growing companies. The companies that use the TaaS model form a team according to the needs of a given project and provide managerial service throughout. Motivated by this new application, we study the Team … Read more

    Planning for Dynamics under Uncertainty

  • Dicong Qiu
  • Karsh Tharyani
    • Categories Dynamic Programming, Systems governed by Differential Equations Optimization, Unconstrained Optimization Tags , ,

    Planning under uncertainty is a frequently encountered problem. Noisy observation is a typical situation that introduces uncertainty. Such a problem can be formulated as a Partially Observable Markov Decision Process (POMDP). However, solving a POMDP is nontrivial and can be computationally expensive in continuous state, action, observation and latent state space. Through this work, we … Read more

    Structure-driven fix-and-propagate heuristics for mixed integer programming

  • Timo Berthold
  • Gerald Gamrath
  • Stefan Heinz
  • Michael Winkler
    • Categories (Mixed) Integer Linear Programming Tags , , , ,

    Primal heuristics play an important role in the solving of mixed integer programs (MIPs). They often provide good feasible solutions early and help to reduce the time needed to prove optimality. In this paper, we present a scheme for start heuristics that can be executed without previous knowledge of an LP solution or a previously … Read more

    Potential-based analyses of first-order methods for constrained and composite optimization

  • Courtney Paquette
  • Stephen A. Vavasis
    • Categories Convex Optimization, Nonsmooth Optimization

    We propose potential-based analyses for first-order algorithms applied to constrained and composite minimization problems. We first propose “idealized” frameworks for algorithms in the strongly and non-strongly convex cases and argue based on a potential that methods following the framework achieve the best possible rate. Then we show that the geometric descent (GD) algorithm by Bubeck … Read more

    An Exact Method for Constrained Maximization of the Conditional Value-at-Risk of a Class of Stochastic Submodular Functions

  • Simge Küçükyavuz
  • Hao-Hsiang Wu
    • Categories Integer Programming, Stochastic Programming

    We consider a class of risk-averse submodular maximization problems (RASM) where the objective is the conditional value-at-risk (CVaR) of a random nondecreasing submodular function at a given risk level. We propose valid inequalities and an exact general method for solving RASM under the assumption that we have an efficient oracle that computes the CVaR of … Read more