Optimization Software and Modeling Systems – Page 22

Scenario-Tree Decomposition: Bounds for Multistage Stochastic Mixed-Integer Programs

Published: 2014/09/16

Integer Programming, Parallel Algorithms, Stochastic Programming bounds, mixed-integer programming, stochastic programming

Multistage stochastic mixed-integer programming is a powerful modeling paradigm appropriate for many problems involving a sequence of discrete decisions under uncertainty; however, they are difficult to solve without exploiting special structures. We present scenario-tree decomposition to establish bounds for unstructured multistage stochastic mixed-integer programs. Our method decomposes the scenario tree into a number of smaller … Read more

RBFOpt: an open-source library for black-box optimization with costly function evaluations

Published: 2014/09/12, Updated: 2018/08/28

Alberto Costa

Giacomo Nannicini

Bound-constrained Optimization, Global Optimization, Optimization Software and Modeling Systems

We consider the problem of optimizing an unknown function given as an oracle over a mixed-integer box-constrained set. We assume that the oracle is expensive to evaluate, so that estimating partial derivatives by finite differences is impractical. In the literature, this is typically called a black-box optimization problem with costly evaluation. This paper describes the … Read more

A scalable bounding method for multi-stage stochastic integer programs

Published: 2014/07/16

Osman Y. Ozaltin

Burhaneddin Sandikçi

Integer Programming, Parallel Algorithms, Stochastic Programming bounding, mixed-integer variables, multi-stage, parallel computing, stochastic programming

Many dynamic decision problems involving uncertainty can be appropriately modeled as multi-stage stochastic programs. However, most practical instances are so large and/or complex that it is impossible to solve them on a single computer, especially due to memory limitations. Extending the work of Sandikci et al. (2013) on two-stage stochastic mixed-integer-programs (SMIPs), this paper develops … Read more

A Non-Parametric Structural Hybrid Modeling Approach for Electricity Prices

Published: 2014/06/30, Updated: 2015/07/14

Ismael Arciniegas Rueda

Finance and Economics, Optimization Software and Modeling Systems, Stochastic Programming

We develop a stochastic model of zonal/regional electricity prices, designed to reflect information in fuel forward curves and aggregated capacity and load as well as zonal or regional price spreads. We use a nonparametric model of the supply stack that captures heat rates and fuel prices for all generators in the market operator territory, combined … Read more

A Parallel Local Search Framework for the Fixed-Charge Multicommodity Network Flow Problem

Published: 2014/06/26, Updated: 2016/08/02

(Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Parallel Algorithms local search heuristic, multi commodity flow, parallel computing

We present a parallel local search approach for obtaining high quality solutions to the Fixed Charge Multi-commodity Network Flow problem (FCMNF). The approach proceeds by improving a given feasible solution by solving restricted instances of the problem where flows of certain commodities are fixed to those in the solution while the other commodities are locally … Read more

How Difficult is Nonlinear Optimization? A Practical Solver Tuning Approach, with Illustrative Results

Published: 2014/06/26

János Pintér

Global Optimization Applications, Nonlinear Optimization, Optimization Software Benchmark

Nonlinear optimization (NLO) per definitionem covers a vast range of problems, from trivial to practically intractable. For this reason, it is impossible to offer “guaranteed” advice to NLO software users. This fact becomes especially obvious, when facing unusually hard and/or previously unexplored NLO challenges. In the present study we offer some related practical observations, propose … Read more

Strict Fejér Monotonicity by Superiorization of Feasibility-Seeking Projection Methods

Published: 2014/05/28

Yair Censor

Alexander J. Zaslavski

Constrained Nonlinear Optimization, Parallel Algorithms bounded perturbation resilience, constrained minimization, convex feasibility problem, dynamic string-averaging projections, strict Fejér monotonicity, subgradients, superiorization methodology, superiorized version of an algorithm

We consider the superiorization methodology, which can be thought of as lying between feasibility-seeking and constrained minimization. It is not quite trying to solve the full fledged constrained minimization problem; rather, the task is to find a feasible point which is superior (with respect to the objective function value) to one returned by a feasibility-seeking … Read more

Parallel Large-Neighborhood Search Techniques for LNG Inventory Routing

Published: 2014/04/17

Badrinarayanan Velamur Asokan

Parallel Algorithms, Supply Chain Management, Transportation

Liquefied natural gas (LNG) is estimated to account for a growing portion of the world natural gas trade. For profitable operation of a capital intensive LNG project, it is necessary to optimally design various aspects of the supply chain associated with it. Of particular interest is optimization of ship schedules and the inventories on the … Read more

Parallel Algorithms for Big Data Optimization

Published: 2014/04/02

Francisco Facchinei

Simone Sagratella

Gesualdo Scutari

Nonlinear Optimization, Nonsmooth Optimization, Parallel Algorithms distributed methods, jacobi method, lasso, parallel optimization, sparse solution

We propose a decomposition framework for the parallel optimization of the sum of a differentiable function and a (block) separable nonsmooth, convex one. The latter term is usually employed to enforce structure in the solution, typically sparsity. Our framework is very flexible and includes both fully parallel Jacobi schemes and Gauss-Seidel (i.e., sequential) ones, as … Read more