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  • © 2009

Natural Intelligence for Scheduling, Planning and Packing Problems

  • Recent research in Natural Intelligence for Scheduling, Planning and Packing Problems

Part of the book series: Studies in Computational Intelligence (SCI, volume 250)

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Table of contents (12 chapters)

  1. Front Matter

  2. Global Optimization in Supply Chain Operations

    • Maksud Ibrahimov, Arvind Mohais, Zbigniew Michalewicz
    Pages 1-28
  3. Solving Real-World Vehicle Routing Problems with Evolutionary Algorithms

    • Thomas Weise, Alexander Podlich, Christian Gorldt
    Pages 29-53
  4. A Genetic Algorithm with Priority Rules for Solving Job-Shop Scheduling Problems

    • S. M. Kamrul Hasan, Ruhul Sarker, Daryl Essam, David Cornforth
    Pages 55-88
  5. An Estimation of Distribution Algorithm for Flowshop Scheduling with Limited Buffers

    • Mansour Eddaly, Bassem Jarboui, Patrick Siarry, Abdelwaheb Rebaï
    Pages 89-110
  6. Electrical Load Forecasting Using a Neural-Fuzzy Approach

    • Ajoy K. Palit, Walter Anheier, Dobrivoje Popovic
    Pages 145-173
  7. Evolutionary and Ant Colony Optimization Based Approaches for a Two-Dimensional Strip Packing Problem

    • Carolina Salto, Guillermo Leguizamón, Enrique Alba, Juan M. Molina
    Pages 245-266
  8. Diagnosis, Configuration, Planning, and Pathfinding: Experiments in Nature-Inspired Optimization

    • W. D. Potter, E. Drucker, P. Bettinger, F. Maier, M. Martin, D. Luper et al.
    Pages 267-294
  9. A Hybrid Intelligent System for Distributed Dynamic Scheduling

    • Ana Madureira, Joaquim Santos, Ivo Pereira
    Pages 295-324
  10. Back Matter

About this book

Scheduling, planning and packing are ubiquitous problems that can be found in a wide range of real-world settings. These problems transpire in a large variety of forms, and have enormous socio-economic impact. For many years, significant work has been devoted to automating the processes of scheduling, planning and packing using different kinds of methods. However, poor scaling and the lack of flexibility of many of the conventional methods coupled with the fact that most of the real-world problems across the application areas of scheduling, planning and packing nowadays tend to be of large scale, dynamic and full of complex dependencies have made it necessary to tackle them in unconventional ways.

This volume, "Natural Intelligence for Scheduling, Planning and Packing Problems", is a collection of numerous natural intelligence based approaches for solving various kinds of scheduling, planning and packing problems. It comprises 12 chapters which present many methods that draw inspiration from nature, such as evolutionary algorithms, neural-fuzzy system, particle swarm algorithms, ant colony optimisation, extremal optimisation, raindrop optimisation, and so on. Problems addressed by these chapters include freight transportation, job shop scheduling, flowshop scheduling, electrical load forecasting, vehicle routing, two-dimensional strip packing, network configuration and forest planning, among others. Along with solving these problems, the contributing authors present a lively discussion of the various aspects of the nature-inspired algorithms utilised, providing very useful and important new insights into the research areas.

Editors and Affiliations

  • School of Computing & Design, Swinburne University of Technology (Sarawak Campus), Kuching, Malaysia

    Raymond Chiong, Sandeep Dhakal

Bibliographic Information

Buy it now

Buying options

eBook USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access