Large Scale Optimization

State of the Art

  • W. W. Hager
  • D. W. Hearn
  • P. M. Pardalos

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Adam J. Berger, John M. Mulvey, Andrzej Ruszczyński
    Pages 1-25
  3. Richard H. Byrd, Thomas Derby, Elizabeth Eskow, Klaas P. B. Oldenkamp, Robert B. Schnabel
    Pages 68-81
  4. Robert Fourer, David M. Gay
    Pages 135-154
  5. Steven A. Gabriel, Jong-Shi Pang
    Pages 155-181
  6. Yusin Lee, James B. Orlin
    Pages 206-244
  7. Costas D. Maranas, Christodoulos A. Floudas
    Pages 259-285
  8. Robert R. Meyer, Jonathan Yackel
    Pages 294-311
  9. Mauricio G. C. Resende, Takashi Tsuchiya, Geraldo Veiga
    Pages 362-387
  10. Suvrajeet Sen, Jason Mai, Julia L. Higle
    Pages 388-410
  11. M. Ap. Tzaferopoulos, E. S. Mistakidis, C. D. Bisbos, P. D. Panagiotopoulos
    Pages 428-456

About this book


On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied Optimization, was held at the University of Florida. The con­ ference was supported by the National Science Foundation, the U. S. Army Research Office, and the University of Florida, with endorsements from SIAM, MPS, ORSA and IMACS. Forty one invited speakers presented papers on mathematical program­ ming and optimal control topics with an emphasis on algorithm development, real world applications and numerical results. Participants from Canada, Japan, Sweden, The Netherlands, Germany, Belgium, Greece, and Denmark gave the meeting an important international component. At­ tendees also included representatives from IBM, American Airlines, US Air, United Parcel Serice, AT & T Bell Labs, Thinking Machines, Army High Performance Com­ puting Research Center, and Argonne National Laboratory. In addition, the NSF sponsored attendance of thirteen graduate students from universities in the United States and abroad. Accurate modeling of scientific problems often leads to the formulation of large­ scale optimization problems involving thousands of continuous and/or discrete vari­ ables. Large scale optimization has seen a dramatic increase in activities in the past decade. This has been a natural consequence of new algorithmic developments and of the increased power of computers. For example, decomposition ideas proposed by G. Dantzig and P. Wolfe in the 1960's, are now implement able in distributed process­ ing systems, and today many optimization codes have been implemented on parallel machines.


algorithms genetic algorithms linear optimization Mathematica mechanics modeling nonlinear optimization optimal control optimization perturbation programming structural mechanics

Editors and affiliations

  • W. W. Hager
    • 1
  • D. W. Hearn
    • 1
  • P. M. Pardalos
    • 1
  1. 1.Center for Applied OptimizationUniversity of FloridaGainesvilleUSA

Bibliographic information