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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
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Journal ArticleDOI
A hybrid genetic approach for channel reuse in multiple access telecommunication networks
TL;DR: The proposed method is based on a hybrid genetic algorithm and aims to accomplish the establishment of a maximal number of connections with the minimal number of isochronous channels, revealing the robustness, the flexibility and the efficiency of using evolutionary approaches to complex real-world problems.
Journal ArticleDOI
An efficient implementation of parallel simulated annealing algorithm in GPUs
TL;DR: A highly optimized version of a simulated annealing (SA) algorithm adapted to the more recently developed graphic processor units (GPUs) with CUDA toolkit, specially designed for Nvidia GPUs is proposed.
Journal ArticleDOI
Optimizing survivability of vulnerable series–parallel multi-state systems
TL;DR: An algorithm based on the universal generating function method is suggested for determination of the vulnerable series–parallel multi-state system survivability and a genetic algorithm is used as optimization tool in order to solve the structure optimization problem.
Proceedings ArticleDOI
On evolution strategy optimization in dynamic environments
Karsten Weicker,Nicole Weicker +1 more
TL;DR: The article analyzes the behavior of evolution strategies and their current mutation variants on a simple rotating dynamic problem and finds the complex covariance matrix adaptation proves to be superior with slow rotation but with increasing dynamism whose adaptation mechanism seldom finds the optimum where the simple uniform adaptation produces stable results.
Journal ArticleDOI
Optimization and Blending of Composite Laminates Using Genetic Algorithms with Migration
TL;DR: The objective function evaluating the fitness of designs is modified according the severity of mismatches detected between neighboring populations, laying the groundwork for natural evolution to a blended global solution without leaving the paradigm of genetic algorithms.