Overview

OmeGA, or the ordering messy genetic algorithm, combines contemporary advances in competent GA technology to solve scheduling and other permutation problems. Competent GAs are those designed for principled solutions of hard problems, quickly, reliably and accurately. Permutation and scheduling problems are difficult combinatorial optimization problems with commercial importance across a variety of industries. This book approaches these subjects systematically and clearly. The first part of the book presents a description of messy GAs along with an innovative adaptation of the method to ordering problems. The second part of the book investigates the algorithm on boundedly difficult test functions, showing principled scale up as problems become harder and longer. Finally, the book applies the algorithm to a test function drawn from the literature of scheduling.

Full Product Details

Author:   Dimitri Knjazew
Publisher:   Springer
Imprint:   Springer
Edition:   2002 ed.
Volume:   6
Dimensions:   Width: 15.50cm , Height: 1.10cm , Length: 23.50cm
Weight:   0.960kg
ISBN:  

9780792374602

ISBN 10:   0792374606
Pages:   152
Publication Date:   31 January 2002
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1. Development of the Omega.- 1.1 The Mechanics of the Fast Messy GA.- 1.2 Using Random Keys for Representation.- 1.3 Designing the OmeGA.- 1.4 Ordering Deceptive Problems.- 1.5 Problem Codings.- 1.6 Experiments.- 1.7 Summary.- 2. Performance Analysis of the Omega.- 2.1 Scale-up Analysis.- 2.2 New Ordering Deceptive Problems.- 2.3 Tests with Uniform and Nonuniform Scaling.- 2.4 Test with Nonuniform Building-Block Size.- 2.5 Tests with Overlapping Building Blocks.- 2.6 Summary.- 3. Application to a Scheduling Problem.- 3.1 Introduction to Scheduling Problems.- 3.2 Problem Formulation.- 3.3 Schedule Representation and Decoding.- 3.4 Experiments.- 3.5 Summary.- 4. Conclusions and Future Work.- Appendices.- Appendix A: The Benchmark Input Data.- Appendix B: Best Schedules.- Appendix C: Source Code of OmeGA.- References.

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