Optimization Techniques for Clustering,Connectivity, and Flow Problems in Complex Networks

Abstract

This project develops network-based optimization methods for solving problems arising in complex system analysis and wireless networking applications. The study of complex systems is of utmost importance for a number of diverse areas of science, engineering and society, including biochemistry, social sciences, epidemiology, transportation, and telecommunications. The project makes contributions to the state of the art of network-based techniques for data mining of complex systems and virtual backbone-based routing in wireless ad hoc networks. The research in this project focused around the following four major thrusts: (I) Theoretical analysis of new models of clusters in networks; (II) Investigating new approaches to virtual backbone-based routing in wireless networks; (III) Establishing techniques for theoretical analysis of heuristics for inapproximable problems and designing new metaheuristic approaches for the problems of interest; (IV) Developing new models and algorithms for robust optimization and decision making in complex networks under uncertainty.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2012
Accession Number
ADA564206

Entities

People

  • Oleg A. Prokopyev
  • Sergiy Butenko
  • Vladimir Boginski

Organizations

  • Texas A&M University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Classification
  • Complex Systems
  • Contracts
  • Electronic Mail
  • Emerging Technology
  • Engineering
  • Industrial Engineering
  • Mathematical Programming
  • Mesh Networks
  • Networks
  • Optimization
  • Sensor Networks
  • Social Sciences
  • Systems Engineering
  • Wireless Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Operations Research
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms