Optimization under Uncertainty and Conflict: Algorithms for Heterogenous Quadratic Programs

Abstract

Theory and methodology for quadratic programs (QPs) are developed. QPs are formulated with different types of variables, objectives and constraint functions. They have single or multiple objectives modeling conflict, and may carry multiple parameters of two types: one type models unknown or uncertain data while the other is required by the proposed algorithms. The new theory includes derivation of relaxations for nonconvex quadratic functions, bilinear functions, and polynomial functions. The developed algorithms rely on an algorithm for solving the multiparametric linear complementarity problem with sufficient matrices and parameters in general positions, which previously was an unsolved problem.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2021
Accession Number
AD1146208

Entities

People

  • Margaret M. Wiecek

Organizations

  • Clemson University

Tags

Communities of Interest

  • Biomedical
  • Cyber
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algebraic Geometry
  • Algorithms
  • Complex Systems
  • Convex Programming
  • Engineering
  • Evolutionary Algorithms
  • Flow Network
  • Integer Programming
  • Linear Programming
  • Mathematical Programming
  • Mathematics
  • Multiobjective Optimization
  • Operations Research
  • Optimization
  • Simplex Method
  • Symposia
  • Systems Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research