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Interfaces in Computer Science and Operations Research

Advances in Metaheuristics, Optimization, and Stochastic Modeling Technologies

  • Book
  • © 1997

Overview

Editors:
  1. Richard S. Barr

    1. Southern Methodist University, Dallas, USA

  2. Richard V. Helgason

    1. Southern Methodist University, Dallas, USA

  3. Jeffery L. Kennington

    1. Southern Methodist University, Dallas, USA

Part of the book series: Operations Research/Computer Science Interfaces Series (ORCS, volume 7)

  • 5832 Accesses

  • 24 Citations

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About this book

The disciplines of computer science and operations research (OR) have been linked since their origins, each contributing to the dramatic advances of the other. This work explores the connections between these key technologies: how high-performance computing methods have led to advances in OR de­ ployment, and how OR has contributed to the design and development of ad­ vanced systems. The collected writings-from researchers and practitioners in Computer Science, Operations Research, Management Science, and Artificial Intelligence-were among those delivered at the Fifth INFORMS Computer Science Technical Section Conference in Dallas, Texas, January 8-10, 1996. The articles advance both theory and practice. Presented are new approaches to complex problems based on: metaheuristics (neural networks, genetic al­ gorithms, and Tabu Search), optimization and mathematical programming, stochastic methods, constraint programming, and logical analysis. These ad­ vanced methodologies are applied to new applications in such areas as: telecom­ munications network design, financial engineering, manufacturing, project man­ agement, and forecasting, airline and machine scheduling, vehicle routing, mod­ eling and decision support systems. Featured is a remarkable paper by keynote speaker Fred Glover, creator of the Tabu Search family of metaheuristics. In it he develops the principles of memory-based heuristic methods, contrasts them with the popular genetic algorithms and simulated annealing, provides a sweeping survey of application vignettes, and points to promising avenues for future research.

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Table of contents (19 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  3. Neural Networks

    1. Neural Networks in Practice: Survey Results

      • Bruce L. Golden, Edward A. Wasil, Steven P. Coy, Cihan H. Dagli
      Pages 77-95

    2. Tractable Theories for the Synthesis of Neural Networks

      • V. Chandru, M. Vidyasagar, V. Vinay
      Pages 97-121

    3. Neural Network Training via Quadratic Programming

      • Theodore B. Trafalis, Nicolas P. Couellan
      Pages 123-139

    4. A Neural Network Model for Predicting Atlantic Hurricane Activity

      • Ohseok Kwon, Bruce Golden, Edward Wasil
      Pages 141-151

  4. Optimization

    1. An Efficient Dual Simplex Optimizer for Generalized Networks

      • Jeffery L. Kennington, Riad A. Mohamed
      Pages 153-182

    2. Solving Large Scale Crew Scheduling Problems

      • Hai D. Chu, Eric Gelman, Ellis L. Johnson
      Pages 183-194

  5. Constraint and Logic Programming

    1. Houria III: A Solver for Hierarchical Systems of Functional Constraints

      • M. Bouzoubaa, B. Neveu, G. Hasle
      Pages 195-215

    2. Some Recent Developments of Using Logical Analysis for Inferring a Boolean Function with Few Clauses

      • Evangelos Triantaphyllou, Boris Kovalerchuk, Aniruddha S. Deshpande
      Pages 217-240

  6. Stochastic Performance Analysis

    1. Computational Analysis of a G/G/1 Queue with Vacations and Exhaustive Service

      • Huan Li, Yixin Zhu
      Pages 241-257

    2. Stability and Queueing-Time Analysis of a Reader-Writer Queue with Writer Preference

      • L. C. Puryear, V. G. Kulkarni
      Pages 259-279

    3. Importance Sampling in Lattice Pricing Models

      • Soren S. Nielsen
      Pages 281-296

  7. Modeling and Decision Support

    1. Data and Optimisation Modelling: A Tool for Elicitation and Browsing (DOME)

      • Hossein Mousavi, Gautam Mitra, Cormac Lucas
      Pages 297-324

    2. Enhancing User Understanding via Model Analysis in a Decision Support System

      • David M. Steiger
      Pages 325-339

  8. Applications in Manufacturing, Logistics, and Finance

    1. Bank Failure Prediction Using Dea to Measure Management Quality

      • Richard S. Barr, Thomas F. Siems
      Pages 341-365

    2. A Cooperative Multi-Agent Approach to Constrained Project Scheduling

      • Dan Zhu, Rema Padman
      Pages 367-382

    3. Scheduling a Flow Shop to Minimize the Maximal Lateness Under Arbitrary Precedence Constraints

      • Joanna Józefowska, Arkadiusz Zimniak
      Pages 383-403

    4. A Genetic Programming Approach for Heuristic Selection in Constrained Project Scheduling

      • Rema Padman, Stephen F. Roehrig
      Pages 405-421

    5. Coupling a Greedy Route Construction Heuristic with a Genetic Algorithm for the Vehicle Routing Problem with Time Windows

      • Jean-Yves Potvin, François Guertin
      Pages 423-442
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Editors and Affiliations

  • Southern Methodist University, Dallas, USA

    Richard S. Barr, Richard V. Helgason, Jeffery L. Kennington

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Bibliographic Information

  • Book Title: Interfaces in Computer Science and Operations Research

  • Book Subtitle: Advances in Metaheuristics, Optimization, and Stochastic Modeling Technologies

  • Editors: Richard S. Barr, Richard V. Helgason, Jeffery L. Kennington

  • Series Title: Operations Research/Computer Science Interfaces Series

  • DOI: https://doi.org/10.1007/978-1-4615-4102-8

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 1997

  • Hardcover ISBN: 978-0-7923-9844-8Published: 31 December 1996

  • Softcover ISBN: 978-1-4613-6837-3Published: 08 October 2012

  • eBook ISBN: 978-1-4615-4102-8Published: 06 December 2012

  • Series ISSN: 1387-666X

  • Series E-ISSN: 2698-5489

  • Edition Number: 1

  • Number of Pages: XII, 442

  • Topics: Operations Research/Decision Theory, Systems Theory, Control, Artificial Intelligence

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