Open AccessBook
Evolutionary algorithms in theory and practice
TLDR
In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming within a unified framework, thereby clarifying the similarities and differences of these methods.About:
The article was published on 1996-01-01 and is currently open access. It has received 2679 citations till now. The article focuses on the topics: Evolutionary music & Evolutionary programming.read more
Citations
More filters
Book ChapterDOI
Evolution Strategy in Portfolio Optimization
TL;DR: In this article, an evolutionary algorithm to optimize a stock portfolio is presented, based on Evolution Strategies, using artificial trading experts discovered by a genetic algorithm, which is tested on a sample of stocks taken from the French market.
Journal ArticleDOI
An evolution-based tabu search approach to codebook design
Shih-Ming Pan,Kuo-Sheng Cheng +1 more
TL;DR: An evolution-based tabu search approach (ETSA) to design codebooks with smaller distortion values in vector quantization and Experimental results show that the ETSA performs better than several existing algorithms in terms of the distortion and robustness measures.
Book ChapterDOI
Hybrid Interior-Langrangian Penalty Based Evolutionary Optimization
Hyun Myung,Jong-Hwan Kim +1 more
TL;DR: An evolutionary optimization method based on a hybrid of an interior penalty and augmented Lagrangian function ensures the generation of feasible solutions during the evolutionary search process with less computation time than required by the interior method.
Journal ArticleDOI
Evolutionary and genetic optimization of NMR gradient and shim coils
TL;DR: In this paper, evolutionary and genetic stochastic optimizations were explored for designing NMR gradient and shim coils, and some hierarchical self-adaptive algorithms, based on a concept of meta-optimization, were tested.
Journal ArticleDOI
Mobility helps problem-solving systems to avoid groupthink.
Paulo F. Gomes,Paulo F. Gomes,Sandro M. Reia,Francisco A. Rodrigues,Francisco A. Rodrigues,José F. Fontanari +5 more
TL;DR: An agent-based model of imitative learning is used to study the influence of the mobility of the agents on the time they require to find the global maxima of NK-fitness landscapes and finds that mobility is slightly harmful for solving easy problems.