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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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Agent-based computational finance: Suggested readings and early research
TL;DR: The use of computer simulated markets with individual adaptive agents in finance is a new, but growing field as mentioned in this paper, focusing on a set of some of the earliest papers in the area.
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GEMDOCK: A generic evolutionary method for molecular docking
Jinn-Moon Yang,Chun Chen Chen +1 more
TL;DR: GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect.
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Memetic algorithms and memetic computing optimization: A literature review
Ferrante Neri,Carlos Cotta +1 more
TL;DR: Several classes of optimization problems, such as discrete, continuous, constrained, multi-objective and characterized by uncertainties, are addressed by indicating the memetic “recipes” proposed in the literature.
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A Trigonometric Mutation Operation to Differential Evolution
Hui-Yuan Fan,Jouni Lampinen +1 more
TL;DR: A new local search operation, trigonometric mutation, is proposed and embedded into the differential evolution algorithm, which enables the algorithm to get a better trade-off between the convergence rate and the robustness.
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Penalty Function Methods for Constrained Optimization with Genetic Algorithms
TL;DR: These penalty-based methods for handling constraints in Genetic Algorithms are presented and discussed and their strengths and weaknesses are discussed.