Accession Number : ADA623076

Title :   Selective Optimization

Descriptive Note : Final rept. Apr 2012-Apr 2015

Corporate Author : GEORGIA TECH RESEARCH CORP ATLANTA

Personal Author(s) : Ahmed, Shabbir ; Dey, Santanu S

PDF Url : ADA623076

Report Date : 06 Jul 2015

Pagination or Media Count : 142

Abstract : This project focuses on developing algorithms for optimization problems that have intrinsic limitations preventing the utilization of all available decision alternatives (problem variables) and/or the satisfaction of all constraints. Part of the optimization decision in these problems is the selection of which variables to use and/or which subset of constraints to satisfy. We refer to these problems as selective optimization (SO) problems. The combinatorial aspects of selection make these problems extremely difficult. In this project we develop a set of generic tools applicable to a wide class of selective optimization problems. Our approach is based on standard mixed-integer programming (MIP) formulations of selective optimization problems.While such formulations can be attacked by commercial optimization solvers, they typically exhibit extremely poor performance. We develop a variety of effective model and algorithm enhancement techniques for the standardMIP formulations. These techniques are easily integrable into commercial MIP solvers, thereby making them readily usable in applications of selective optimization.

Descriptors :   *LINEAR PROGRAMMING, *OPTIMIZATION, ALGORITHMS, COMBINATORIAL ANALYSIS, DECISION MAKING, DISTRIBUTED COMPUTING, FUNCTIONS(MATHEMATICS), GAUSSIAN NOISE, NONLINEAR SYSTEMS, PERFORMANCE(ENGINEERING), PROBABILITY, RANDOM VARIABLES, STOCHASTIC PROCESSES, VECTOR ANALYSIS

Subject Categories : Statistics and Probability
      Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE