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
Journal ArticleDOI
The safety-factor calibration of laminates for long-term applications: behavior model and reliability method
Fabrice Richard,D. Perreux +1 more
TL;DR: In this article, a damaged elasto-viscoplastic model is presented to predict the behavior of a layer made of a polymer reinforced with unidirectional fibers.
Journal ArticleDOI
Control design of spinning rockets based on co-evolutionary optimization
TL;DR: In this paper, a proportional, integral, and derivative (PID) type controller for a spinning sounding rocket is developed for a dynamic model simplified by a complex summation method.
Journal ArticleDOI
Bayesian Methods for Efficient Genetic Programming
TL;DR: A Bayesian framework for genetic programming (GP) is presented and two GP algorithms derived from the Bayesian GP framework are presented, one is the genetic programming with the adaptive Occam's razor (AOR) designed to evolve parsimonious programs and the other is the Genetic programming with incremental data inheritance (IDI), designed to accelerate evolution by active selection of fitness cases.
Journal ArticleDOI
Sequential and multi-population memetic algorithms for assigning cells to switches in mobile networks
Alejandro Quintero,Samuel Pierre +1 more
TL;DR: The results obtained confirm the efficiency and the effectiveness of MA to provide good solutions for moderate- and large-sized cellular mobile networks, in comparison with standard genetic algorithm and with other heuristic methods well known in the literature.
Book ChapterDOI
Resource Allocation for Steerable Parallel Parameter Searches
TL;DR: This paper presents a model for user-directed searches, and proposes a number of resource allocation strategies and evaluates them in simulation to find that prioritizing the assignments of tasks to compute resources throughout the search can lead to substantial performance improvements.