Multi-objectivization in Evolutionary Algorithms - Softcover

Lochtefeld, Darrell

Softcover

ISBN 10: 3845428546 ISBN 13: 9783845428543

Publisher: LAP LAMBERT Academic Publishing, 2011

Synopsis

Multi-objectivization is the process of reformulating a single-objective problem into a multi-objective problem and solving it with a multi-objective method in order to provide a solution to the original single-objective problem. This work investigates Evolutionary Algorithms (EAs) in both a general categorical sense and as they are applied to multi-objectivization. A diversity classification framework for EAs is proposed. Furthermore, multi-objectivization techniques are examined. Through study of an abstract problem, job-shop scheduling problems, and the Traveling Salesman Problem, principles governing the design decisions for multi-objectivization are identified. Two ways in which multi-objectivization creates beneficial search results are theorized. Prevalent multi-objectivization techniques are compared both analytically and through these experiments. A third, more general version of the studied techniques is proposed with results showing robust performance across a variety of computational budgets.

About this title

About the Author

Darrell Lochtefeld graduated with a Ph.D. in Engineering (Industrial and Human Systems) from Wright State University, Dayton Ohio in June, 2011. His professional interests include modeling and simulation, optimization, machine learning, and software design.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2011
• ISBN 10: 3845428546
• ISBN 13: 9783845428543
• Binding: Paperback
• Language: English
• Number of pages: 256