Peste 4 milioane de titluri în engleză și alte limbi! Descoperă-ți noua poveste astăzi!

Scatter Search

Name: Scatter Search
Brand: Springer-Verlag New York Inc.
SKU: 9781461350279
Price: 826.98 RON
Availability: InStock

Methodology and Implementations in C

Autor: Manuel Laguna, Rafael Martí

Limbă:

Legare: Carte broșată

Editura: Springer-Verlag New York Inc.

Disponibilitate: În depozitul extern

Expediem în 5-8 zile

826.98 lei

The book Scatter Search by Manuel Laguna and Rafael Mart! represents a long-awaited "missing link" i...

Informații despre carte

Autor

Manuel Laguna, Rafael Martí

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2012

Pagini

291

EAN

9781461350279

ISBN

1461350271

Enbook ID

06796170

Editura

Springer-Verlag New York Inc.

Greutate

480

Dimensiuni

155 x 235 x 17

Descriere completă

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.