Cargando…

Recent Advances in Evolutionary Computation for Combinatorial Optimization

Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metahe...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Cotta, Carlos (Editor ), van Hemert, Jano (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Studies in Computational Intelligence, 153
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-3-540-70807-0
003 DE-He213
005 20220118073550.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 |a 9783540708070  |9 978-3-540-70807-0 
024 7 |a 10.1007/978-3-540-70807-0  |2 doi 
050 4 |a TA345-345.5 
072 7 |a UGC  |2 bicssc 
072 7 |a COM007000  |2 bisacsh 
072 7 |a UGC  |2 thema 
082 0 4 |a 670.285  |2 23 
245 1 0 |a Recent Advances in Evolutionary Computation for Combinatorial Optimization  |h [electronic resource] /  |c edited by Carlos Cotta, Jano van Hemert. 
250 |a 1st ed. 2008. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2008. 
300 |a XVII, 337 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 153 
505 0 |a Theory and Methodology -- An Evolutionary Algorithm for the Solution of Two-Variable Word Equations in Partially Commutative Groups -- Determining Whether a Problem Characteristic Affects Heuristic Performance -- Performance and Scalability of Genetic Algorithms on NK-Landscapes -- Engineering Stochastic Local Search Algorithms: A Case Study in Estimation-Based Local Search for the Probabilistic Travelling Salesman Problem -- Hybrid Approaches -- A Lagrangian Decomposition/Evolutionary Algorithm Hybrid for the Knapsack Constrained Maximum Spanning Tree Problem -- A Hybrid Optimization Framework for Cutting and Packing Problems -- A Hybrid Genetic Algorithm for the DNA Fragment Assembly Problem -- A Memetic-Neural Approach to Discover Resources in P2P Networks -- Constrained Problems -- An Iterative Heuristic Algorithm for Tree Decomposition -- Search Intensification in Metaheuristics for Solving the Automatic Frequency Problem in GSM -- Contraction-Based Heuristics to Improve the Efficiency of Algorithms Solving the Graph Colouring Problem -- Scheduling -- Different Codifications and Metaheuristic Algorithms for the Resource Renting Problem with Minimum and Maximum Time Lags -- A Simple Optimised Search Heuristic for the Job Shop Scheduling Problem -- Parallel Memetic Algorithms for Independent Job Scheduling in Computational Grids -- Routing and Travelling Salesman Problems -- Reducing the Size of Travelling Salesman Problem Instances by Fixing Edges -- Algorithms for Large Directed Capacitated Arc Routing Problem Instances -- An Evolutionary Algorithm with Distance Measure for the Split Delivery Capacitated Arc Routing Problem -- A Permutation Coding with Heuristics for the Uncapacitated Facility Location Problem. 
520 |a Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems. The application of metaheuristics to combinatorial optimisation is an active field in which new theoretical developments, new algorithmic models, and new application areas are continuously emerging. This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches. In this sense, the book includes cutting-edge theoretical, methodological, algorithmic and applied developments in the field, from respected experts and with a sound perspective. 
650 0 |a Computer-aided engineering. 
650 0 |a Software engineering. 
650 0 |a Operations research. 
650 0 |a Engineering mathematics. 
650 0 |a Engineering-Data processing. 
650 1 4 |a Computer-Aided Engineering (CAD, CAE) and Design. 
650 2 4 |a Software Engineering. 
650 2 4 |a Operations Research and Decision Theory. 
650 2 4 |a Mathematical and Computational Engineering Applications. 
700 1 |a Cotta, Carlos.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a van Hemert, Jano.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783540867005 
776 0 8 |i Printed edition:  |z 9783642089732 
776 0 8 |i Printed edition:  |z 9783540708063 
830 0 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 153 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-540-70807-0  |z Texto Completo 
912 |a ZDB-2-ENG 
912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)