Overview
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (14 chapters)
-
Front Matter
-
Back Matter
Keywords
About this book
Multiobjective flowshops, job shops and open shops are each highly relevant models in manufacturing, classroom scheduling or automotive assembly, yet for want of sound methods they have remained almost untouched to date. This text shows how methods such as Elitist Nondominated Sorting Genetic Algorithm (ENGA) can find a bevy of Pareto optimal solutions for them. Also it accents the value of hybridizing Gas with both solution-generating and solution-improvement methods. It envisions fundamental research into such methods, greatly strengthening the growing reach of metaheuristic methods.
This book is therefore intended for students of industrial engineering, operations research, operations management and computer science, as well as practitioners. It may also assist in the development of efficient shop management software tools for schedulers and production planners who face multiple planning and operating objectives as a matter of course.
Authors and Affiliations
Bibliographic Information
Book Title: Multiobjective Scheduling by Genetic Algorithms
Authors: Tapan P. Bagchi
DOI: https://doi.org/10.1007/978-1-4615-5237-6
Publisher: Springer New York, NY
-
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1999
Hardcover ISBN: 978-0-7923-8561-5Published: 31 August 1999
Softcover ISBN: 978-1-4613-7387-2Published: 29 October 2012
eBook ISBN: 978-1-4615-5237-6Published: 06 December 2012
Edition Number: 1
Number of Pages: XIII, 358
Topics: Operations Management, Operations Research/Decision Theory