Overview
- 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)
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Front Matter
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Back Matter
Keywords
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
Bibliographic Information
Book Title: Natural Intelligence for Scheduling, Planning and Packing Problems
Editors: Raymond Chiong, Sandeep Dhakal
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-04039-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2009
Hardcover ISBN: 978-3-642-04038-2Published: 30 September 2009
Softcover ISBN: 978-3-642-26061-2Published: 14 March 2012
eBook ISBN: 978-3-642-04039-9Published: 18 November 2009
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 329
Topics: Artificial Intelligence, Operations Management, IT in Business, Mathematical and Computational Engineering, Operations Research/Decision Theory