| 000 | 00899camuu2200265 a 4500 | |
| 001 | 000045404585 | |
| 005 | 20071204150537 | |
| 008 | 071130s2007 gw a b 001 0 eng d | |
| 020 | ▼a 9783540732969 | |
| 020 | ▼a 3540732969 | |
| 040 | ▼a BTCTA ▼c BTCTA ▼d YDXCP ▼d BAKER ▼d Uk ▼d 211009 | |
| 082 | 0 4 | ▼a 005.1 ▼2 22 |
| 090 | ▼a 005.1 ▼b H992 | |
| 245 | 0 0 | ▼a Hybrid evolutionary algorithms / ▼c Crina Grosan, Ajith Abraham, Hisao Ishibuchi (eds.). |
| 260 | ▼a Berlin : ▼b Springer , ▼c c2007. | |
| 300 | ▼a xv, 403 p. : ▼b ill. ; ▼c 25 cm. | |
| 440 | 0 | ▼a Studies in computational intelligence ; ▼v 75 |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Evolutionary programming (Computer science) |
| 650 | 0 | ▼a Computer algorithms. |
| 700 | 1 | ▼a Grosan, Crina. |
| 700 | 1 | ▼a Abraham, Ajith , ▼d 1968- |
| 700 | 1 | ▼a Ishibuchi, Hisao. |
| 945 | ▼a KINS |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 005.1 H992 | 등록번호 121161090 (1회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
This edited volume is targeted at presenting the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms". The chapters deal with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. Overall, the book has 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. The contributions were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in “Hybrid Evolutionary Algorithms”. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
New feature
Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in ’Hybrid Evolutionary Algorithms’. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
정보제공 :
목차
Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews.- Quantum-Inspired Evolutionary Algorithm for Numerical Optimization.- Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective.- Hybrid Evolutionary Algorithms and Clustering Search.- A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy.- An Efficient Nearest Neighbor Classifier.- Hybrid Genetic: Particle Swarm Optimization Algorithm.- A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection.- Memetic Algorithms Parametric Optimization for Microlithography.- Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction.- A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids.- Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search.- Robust Parametric Image Registration.- Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP.
정보제공 :