Constraint-Handling in Evolutionary Optimization

Description: Constraint-Handling in Evolutionary Optimization Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Efren Mezura-Montes Format: Hardback Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Germany Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K ISBN-13: 9783642006180, 978-3642006180 Synopsis Evolutionary algorithms (EAs), as well as other bio-inspired heuristics, are widely usedto [url] or- inal versions, they are limited to unconstrained search spaces [url] they do not include a mechanism to incorporate feasibility information into the ?tness function. On the other hand, real-world problems usually have constraints in their models. Therefore, a considerable amount of research has been d- icated to design and implement constraint-handling techniques. The use of (exterior) penalty functions is one of the most popular methods to deal with constrained search spaces when using EAs. However, other alternative me- ods have been proposed such as: special encodings and operators, decoders, the use of multiobjective concepts, among others. An e?cient and adequate constraint-handling technique is a key element in the design of competitive evolutionary algorithms to solve complex op- mization problems. In this way, this subject deserves special research e?orts. After asuccessfulspecialsessiononconstraint-handlingtechniquesusedin evolutionary algorithms within the Congress on Evolutionary Computation (CEC) in 2007, and motivated by the kind invitation made by Dr. Janusz Kacprzyk, I decided to edit a book, with the aim of putting together recent studies on constrained numerical optimization using evolutionary algorithms and other bio-inspired approaches. The intended audience for this book comprises graduate students, prac- tionersandresearchersinterestedonalternativetechniquestosolvenumerical optimization problems in presence of constraints.

Price: 73.32 GBP

Location: Aldershot

End Time: 2024-09-28T08:00:32.000Z

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