Scatter Search: Methodology and Implementations in C Softcover Repri Edition Contributor(s): Laguna, Manuel (Author), Martí, Rafael (Author) |
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ISBN: 1402073763 ISBN-13: 9781402073762 Publisher: Springer OUR PRICE: $104.49 Product Type: Paperback - Other Formats Published: February 2003 Annotation: The evolutionary approach called scatter search originated from strategies for creating composite decision rules and surrogate constraints. Recent studies demonstrate the practical advantages of this approach for solving a diverse array of optimization problems from both classical and real world settings. Scatter search contrasts with other evolutionary procedures, such as genetic algorithms, by providing unifying principles for joining solutions based on generalized path constructions in Euclidean space and by utilizing strategic designs where other approaches resort to randomization. The book's goal is to provide the basic principles and fundamental ideas that will allow the readers to create successful applications of scatter search. The book includes the C source code of the methods introduced in each chapter. From the Foreword: |
Additional Information |
BISAC Categories: - Computers | Programming - General - Mathematics | Linear & Nonlinear Programming - Computers | Intelligence (ai) & Semantics |
Dewey: 005.1 |
LCCN: 2002044444 |
Series: Operations Research/Computer Science Interfaces |
Physical Information: 0.95" H x 6.32" W x 9.7" (1.50 lbs) 291 pages |
Descriptions, Reviews, Etc. |
Publisher Description: The book Scatter Search by Manuel Laguna and Rafael Mart represents a long-awaited "missing link" in the literature of evolutionary methods. Scatter Search (SS)-together with its generalized form called Path Relinking-constitutes the only evolutionary approach that embraces a collection of principles from Tabu Search (TS), an approach popularly regarded to be divorced from evolutionary procedures. The TS perspective, which is responsible for introducing adaptive memory strategies into the metaheuristic literature (at purposeful level beyond simple inheritance mechanisms), may at first seem to be at odds with population-based approaches. Yet this perspective equips SS with a remarkably effective foundation for solving a wide range of practical problems. The successes documented by Scatter Search come not so much from the adoption of adaptive memory in the range of ways proposed in Tabu Search (except where, as often happens, SS is advantageously coupled with TS), but from the use of strategic ideas initially proposed for exploiting adaptive memory, which blend harmoniously with the structure of Scatter Search. From a historical perspective, the dedicated use of heuristic strategies both to guide the process of combining solutions and to enhance the quality of offspring has been heralded as a key innovation in evolutionary methods, giving rise to what are sometimes called "hybrid" (or "memetic") evolutionary procedures. The underlying processes have been introduced into the mainstream of evolutionary methods (such as genetic algorithms, for example) by a series of gradual steps beginning in the late 1980s. |