A Particle Swarm Pattern Search Method for Bound Constrained Nonlinear Optimization

In this paper we develop, analyze, and test a new algorithm for the global minimization of a function subject to simple bounds without the use of derivatives. The underlying algorithm is a pattern search method, more specifically a coordinate search method, which guarantees convergence to stationary points from arbitrary starting points. In the optional search … Read more

Benchmark of Some Nonsmooth Optimization Solvers for Computing Nonconvex Proximal Points

The major focus of this work is to compare several methods for computing the proximal point of a nonconvex function via numerical testing. To do this, we introduce two techniques for randomly generating challenging nonconvex test functions, as well as two very specific test functions which should be of future interest to Nonconvex Optimization Benchmarking. … Read more

TTTPLOTS: A perl program to create time-to-target plots

This papers describes a perl language program to create time-to-target solution value plots for measured CPU times that are assumed to fit a shifted exponential distribution. This is often the case in local search based heuristics for combinatorial optimization, such as simulated annealing, genetic algorithms, iterated local search, tabu search, WalkSAT, and GRASP. Such plots … Read more

Benchmarking Optimization Software with COPS 3.0

We describe version 3.0 of the COPS set of nonlinearly constrained optimization problems. We have added new problems, as well as streamlined and improved most of the problems. We also provide a comparison of the FILTER, KNITRO, LOQO, MINOS, and SNOPT solvers on these problems. Citation Technical Report ANL/MCS-TM-273, Argonne National Laboratory, 02/04. Article Download … Read more

On Implementing Self-Regular Proximity Based Feasible IPMs

Self-regular based interior point methods present a unified novel approach for solving linear optimization and conic optimization problems. So far it was not known if the new Self-Regular IPMs can lead to similar advances in computational practice as shown in the theoretical analysis. In this paper, we present our experiences in developing the software package … Read more

A Server for Automated Performance Analysis of Benchmarking Data

As part of Performance World, we describe an automation server (PAVER: http://www.gamsworld.org/performance/paver) to help facilitate reproducible performance analysis of benchmarking data for optimization software. Although PAVER does not solve optimization problems, it automates the task of performance data analysis and visualization, taking into account various performance metrics. These include not only robustness and efficiency, but … Read more

An Active-Set Algorithm for Nonlinear Programming Using Linear Programming and Equality Constrained Subproblems

This paper describes an active-set algorithm for large-scale nonlinear programming based on the successive linear programming method proposed by Fletcher and Sainz de la Maza. The step computation is performed in two stages. In the first stage a linear program is solved to estimate the active set at the solution. The linear program is obtained … Read more

Numerical experience with solving MPECs as NLPs

This paper describes numerical experience with solving MPECs as NLPs on a large collection of test problems. The key idea is to use off-the-shelf NLP solvers to tackle large instances of MPECs. It is shown that SQP methods are very well suited to solving MPECs and at present outperform Interior Point solvers both in terms … Read more

CUTEr (and SifDec), a Constrained and Unconstrained Testing Environment, revisited

The initial release of CUTE, a widely used testing environment for optimization software was described by Bongartz, Conn, Gould and Toint. The latest version, now known as CUTEr, is presented. New features include reorganisation of the environment to allow simultaneous multi-platform installation, new tools for, and interfaces to, optimization packages, and a considerably simplified and … Read more