Solving the p -Median Problem with a Semi-Lagrangian Relaxation

Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a minimization problem. We study a modified Lagrangian relaxation which generates an optimal integer solution. We call it semi-Lagrangian relaxation and illustrate its practical value by solving large-scale instances of the p-median proble

Semi-Lagrangian Relaxation

Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a minimization problem. We propose a modified Lagrangian relaxation which used in (linear) combinatorial optimization with equality constraints generates an optimal intinteger solution. We call this new concept semi-Lagrangian relaxation and illustrate its practical value by solving large-scale instances of the p-median problem

Proximal-Accpm : a versatile oracle based optimization method

Oracle Based Optimization (OBO) conveniently designates an approach to handle a class of convex optimization problems in which the information pertaining to the function to be minimized and/or to the feasible set takes the form of a linear outer approximation revealed by an oracle. We show, through three representative examples, how difficult problems can be cast in this format, and solved. We present an efficient method, Proximal-ACCPM, to trigger the OBO approach and give a snapshot on numerical results. This paper summarizes several contributions with the OBO approach and aims to give, in a single report, enough information on the method and its implementation to facilitate new applications

Parallelization of the algebraic path problem on linear SIMD/SPMD arrays

Theme 1 - Reseaux et systemes - Projet COSIAvailable from INIST (FR), Document Supply Service, under shelf-number : 22588, issue : a.2001 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc