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
Neural networks in finance
TL;DR: McNelis as mentioned in this paper explores the intuitive appeal of neural networks and the genetic algorithm in finance and demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction.
Journal ArticleDOI
Benchmarking discrete optimization heuristics with IOHprofiler
TL;DR: This work compiles and assess a selection of 23 discrete optimization problems that subscribe to different types of fitness landscapes, and provides a new module for IOHprofiler which extents the fixed-target and fixed-budget results for the individual problems by ECDF results, which allows one to derive aggregated performance statistics for groups of problems.
Journal ArticleDOI
Workforce‐constrained Preventive Maintenance Scheduling Using Evolution Strategies
TL;DR: Comparison of evolution strategies and simulated annealing for the 852 experiments indicated much faster convergence to optimality with evolution strategies, which empirically supported practical utility of evolution Strategies to solve large-scale, complex preventive maintenance problems involving single- and multiple-skilled workforce.
Proceedings ArticleDOI
An adaptive genetic fuzzy multi-path routing protocol for wireless ad-hoc networks
TL;DR: GFMRP naturally deals with the uncertainty in MANET and adaptively constructs a set of highly reliable paths by considering the interplays among multiple route selection parameters, which is a multi-path routing protocol based on fuzzy set theory and evolutionary computing.
Journal ArticleDOI
Electromagnetic Optimization Using Mixed-Parameter and Multiobjective Covariance Matrix Adaptation Evolution Strategy
Elie BouDaher,Ahmad Hoorfar +1 more
TL;DR: In this paper, two different schemes for the implementation of mixed-parameter covariance matrix adaptation evolution strategy (CMA-ES) for the design and optimization of electromagnetic (EM) problems are presented.