Selective Optimization

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.

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Document Details

Document Type
Technical Report
Publication Date
Jul 06, 2015
Accession Number
ADA623076

Entities

People

  • Santanu S. Dey
  • Shabbir Ahmed

Organizations

  • Georgia Tech Research Corporation

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Applied Mathematics
  • Computer Programming
  • Construction
  • Electronic Mail
  • Integer Programming
  • Linear Programming
  • Mathematics
  • Operations Research
  • Optimization
  • Probability
  • Probability Distributions
  • Random Variables
  • Simplex Method
  • Standards
  • Systems Engineering

Fields of Study

  • Computer science

Readers

  • Operations Research
  • Systems Analysis and Design