Block-Iterative Algorithms with Underrelaxed Bregman Projections

The notion of relaxation is well understood for orthogonal projections onto convex sets. For general Bregman projections it was considered only for hyperplanes and the question of how to relax Bregman projections onto convex sets that are not linear (i.e., not hyperplanes or half-spaces) has remained open. A definition of underrelaxation of Bregman projections onto … Read more

A New Mathematical-Programming Framework for Facility-Layout Design

We present a new framework for efficiently finding competitive solutions for the facility-layout problem. This framework is based on the combination of two new mathematical-programming models. The first model is a relaxation of the layout problem and is intended to find good starting points for the iterative algorithm used to solve the second model. The … Read more

A Note on Approximating the 2-Catalog Segmentation Problem

We present a $.73$-approximation algorithm for a disjoint $2$-Catalog Segmentation and $.63$-approximation algorithm for the joint version of the problem. Previously best known results are $.65$ and $.56$, respectively. The results are based on semidefinite programming and a subtle rounding method. CitationWorking Paper, Department of Management Sciences, Henry, B. Tippie College of Business, The University … Read more

A hybrid improvement heuristic for the one-dimensional bin packing problem

We propose in this work a hybrid improvement procedure for the bin packing problem. This heuristic has several features: the use of lower bounding strategies; the generation of initial solutions by reference to the dual min-max problem; the use of load redistribution based on dominance, differencing, and unbalancing; and the inclusion of an improvement process … Read more

A GRASP heuristic for the capacitated minimum spanning tree problem using a memory-based local search strategy

We describe a new neighborhood structure for the capacitated minimum spanning tree problem. This neighborhood structure is used by a local search strategy, leading to good trade-offs between solution quality and computation time. We also propose a GRASP with path-relinking heuristic. It uses a randomized version of a savings heuristic in the construction phase and … Read more

Optimality Conditions for Vector Optimization with Set-Valued Maps

Based on near convexity, we introduce the concepts of nearly convexlike set-valued maps and nearly semiconvexlike set-valued maps, give some charaterizations of them, and investigate the relationships between them. Then a Farkas-Minkowski type alternative theorem is shown under the assumption of near semiconvexlikeness. By using the alternative theorem and some other lemmas, we establish necessary … Read more

Global Optimization: Software, Test Problems, and Applications

We provide a concise review of the most prominent global optimization (GO) strategies currently available. This is followed by a discussion of GO software, test problems and several important types of applications, with additional pointers. The exposition is concentrated around topics related to continuous GO, although in certain aspects it is also pertinent to analogous … Read more

Recovery of the Analytic Center in Perturbed Quadratic Regions and Applications

We present results to recover an approximate analytic center when a sectional convex quadratic set is perturbed by a finite number of new quadratic inequalities. This kind of restarting may play an important role in some interior-point algorithms that successively refine the region where is the solution of the original problem. CitationTechnical Repor ES 508-99, … Read more

The method of reflection-projection for convex feasibility problems with an obtuse cone

The convex feasibility problem asks to find a point in the intersection of finitely many closed convex sets in Euclidean space. This problem is of fundamental importance in mathematics and physical sciences, and it can be solved algorithmically by the classical method of cyclic projections. In this paper, the case where one of the constraints … Read more

GloptiPoly – Global Optimization over Polynomials withMatlab and SeDuMi

GloptiPoly is a Matlab/SeDuMi add-on to build and solve convex linear matrix inequality relaxations of the (generally non-convex) global optimization problem of minimizing a multivariable polynomial function subject to polynomial inequality, equality or integer constraints. It generates a series of lower bounds monotonically converging to the global optimum. Numerical experiments show that for most of … Read more