Optimization and Industry: New Frontiers

  • Panos M. Pardalos
  • Victor Korotkikh

Part of the Applied Optimization book series (APOP, volume 78)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Sharon K. Filipowski, Matthew E. Berge, Daniel J. Pierce, Jason Wu
    Pages 1-13
  3. Burak Eksioglu, Athanasios Migdalas, Panos M. Pardalos
    Pages 15-37
  4. Donald R. Jones
    Pages 39-58
  5. Mauricio G. C. Resende
    Pages 59-112
  6. Jerzy A. Filar, Prabhu Manyem, Marc Simon Visser, Kevin White
    Pages 113-140
  7. Manuel Iori, Silvano Martello, Michele Monaci
    Pages 159-179
  8. Galina Korotkikh, Victor Korotkikh
    Pages 181-219
  9. M. M. Ali, C. Oppermann, B. Thomas, E. M. Wolmarans
    Pages 241-257
  10. Baolin Wu, Xinghuo Yu
    Pages 281-292
  11. Michael J. Nealon, Mark E. Johnston
    Pages 309-326

About this book

Introduction

Optimization from Human Genes to Cutting Edge Technologies The challenges faced by industry today are so complex that they can only be solved through the help and participation of optimization ex­ perts. For example, many industries in e-commerce, finance, medicine, and engineering, face several computational challenges due to the mas­ sive data sets that arise in their applications. Some of the challenges include, extended memory algorithms and data structures, new program­ ming environments, software systems, cryptographic protocols, storage devices, data compression, mathematical and statistical methods for knowledge mining, and information visualization. With advances in computer and information systems technologies, and many interdisci­ plinary efforts, many of the "data avalanche challenges" are beginning to be addressed. Optimization is the most crucial component in these efforts. Nowadays, the main task of optimization is to investigate the cutting edge frontiers of these technologies and systems and find the best solutions for their realization. Optimization principles are evident in nature (the perfect optimizer) and appeared early in human history. Did you ever watch how a spider catches a fly or a mosquito? Usually a spider hides at the edge of its net. When a fly or a mosquito hits the net the spider will pick up each line in the net to choose the tense line? Some biologists explain that the line gives the shortest path from the spider to its prey.

Keywords

algorithms combinatorial optimization communication network computer data structures decision support global optimization Mathematica metaheuristic optimization sets Simulation statistical method telecommunications visualization

Editors and affiliations

  • Panos M. Pardalos
    • 1
  • Victor Korotkikh
    • 2
  1. 1.University of FloridaGainesvilleUSA
  2. 2.Central Queensland UniversityMackayAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4613-0233-9
  • Copyright Information Springer-Verlag US 2003
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7953-9
  • Online ISBN 978-1-4613-0233-9
  • Series Print ISSN 1384-6485
  • About this book