Optimization Algorithms for New Computer Architectures with Applications to Routing and Scheduling

Abstract

Many Air Force applications can be modeled as some extension of a pure network problem. These extensions may require additional side constraints, arcs that involve attrition or flow of multiple commodities on a single arc. In all cases, the network models require integer programming model. Since some of these applications demand computer hardware several orders of magnitude faster than the fastest machines available, we have investigated the use of parallelism to increase the computational speed of these algorithms. Very powerful hardware (in terms of millions of floating point operations per second) can be built using many low cost standard chips, all designed to operate in parallel. Our research program objective is to develop and empirically test new serial and parallel algorithms and software for network based models. The problems studied during the past eighteen months include the generalized network problem, the transportation problem, sparse and dense assignment problems, the one-to-one shortest path problem problem, and the singly constrained assignment problem. Algorithms for all of these models have been developed and empirically tested on a variety of sequential and parallel computers.

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Document Details

Document Type
Technical Report
Publication Date
Feb 20, 1992
Accession Number
ADA251959

Entities

People

  • Jeffrey L. Kennington

Organizations

  • Southern Methodist University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Applied Mathematics
  • Artificial Intelligence
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Department Of Defense
  • Engineering
  • Integer Programming
  • Linear Programming
  • Mathematical Programming
  • Operating Systems
  • Operations Research
  • Parallel Computing
  • Simplex Method

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Graph Algorithms and Convex Optimization.
  • Parallel and Distributed Computing.