Multi-Objective Memetic Algorithms
The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories,...
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| Main Author: | |
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| Other Authors: | , , |
| Format: | Livre numérique |
| Language: | Anglais |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edition: | 1st ed. 2009. |
| Series: | Studies in Computational Intelligence
171 |
| Online Access: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Multi-objective memetic algorithms, Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan, Berlin, Springer, 2009, 1 vol. (XII-402 p.), Studies in computational intelligence, 978-3-540-88050-9 |
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| 082 | |a 519 | ||
| 100 | 1 | |a Kacprzyk, Janusz, |d 1947- | |
| 245 | 1 | 0 | |a Multi-Objective Memetic Algorithms |c edited by Janusz Kacprzyk, Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan. |
| 250 | |a 1st ed. 2009. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 171 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Evolutionary Multi-Multi-Objective Optimization - EMMOO Implementation of Multiobjective Memetic Algorithms for Combinatorial Optimization Problems: A Knapsack Problem Case Study Knowledge Infused in Design of Problem-Specific Operators Solving Time-Tabling Problems Using Evolutionary Algorithms and Heuristics Search An Efficient Genetic Algorithm with Uniform Crossover for the Multi-Objective Airport Gate Assignment Problem Application of Evolutionary Algorithms for Solving Multi-Objective Simulation Optimization Problems Feature Selection Using Single/Multi-Objective Memetic Frameworks Multi-Objective Robust Optimization Assisted by Response Surface Approximation and Visual Data-Mining Multiobjective Metamodel Assisted Memetic Algorithms A Convergence Acceleration Technique for Multiobjective Optimisation Knowledge Propagation through Cultural Evolution Risk and Cost Tradeoff in Economic Dispatch Including Wind Power Penetration Based on Multi-Objective Memetic Particle Swarm Optimization Hybrid Behavioral-Based Multiobjective Space Trajectory Optimization Nature-Inspired Particle Mechanics Algorithm for Multi-Objective Optimization Information Exploited for Local Improvement Combination of Genetic Algorithms and Evolution Strategies with Self-adaptive Switching Comparison between MOEA/D and NSGA-II on the Multi-Objective Travelling Salesman Problem Integrating Cross-Dominance Adaptation in Multi-Objective Memetic Algorithms A Memetic Algorithm for Dynamic Multiobjective Optimization A Memetic Coevolutionary Multi-Objective Differential Evolution Algorithm Multiobjective Memetic Algorithm and Its Application in Robust Airfoil Shape Optimization | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization | ||
| 700 | 1 | |a Tan, Kay Chen. |4 pbd | |
| 700 | 1 | |a Goh, Chi-Keong. |4 pbd | |
| 700 | 1 | |a Ong, Yew-Soon. |4 pbd | |
| 776 | 0 | |0 147815231 |t Multi-objective memetic algorithms |f Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan |c Berlin |n Springer |d 2009 |p 1 vol. (XII-402 p.) |s Studies in computational intelligence |z 978-3-540-88050-9 | |
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| 856 | 4 | |5 180339901:750867612 |u https://ezproxy.insa-cvl.fr/login?qurl=https://dx.doi.org/10.1007/978-3-540-88051-6 |z Accès INSA CVL | |
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