Practical Genetic Algorithms

By C. Anderson‐Cook. 2005

2,740 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/2b3dc032df95539d612b7e7f5ed9915dbbcfd6b9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jeff Clune
2. Kenneth O. Stanley
3. Joel Lehman
4. Mengjie Zhang
5. Bing Xue
6. Yanan Sun
7. Gary G. Yen
8. Sebastian Risi

In Computational Theory and Mathematics

1. Bing Xue
2. Mengjie Zhang
3. Yanan Sun
4. Gary G. Yen
5. Jiancheng Lv
6. Ming‐Shyan Huang
7. Hossein Nezamabadi-pour
8. Roberto Sepúlveda

Citations in the corpus

• GA: A Package for Genetic Algorithms in R (2013, background): “Genetic algorithms Genetic algorithms are stochastic search algorithms which are able to solve optimization problems of the type described in Equation 1, both for continuous (whether di↵erentiable or not) and discrete functions (A↵enzeller and Winkler 2009; Back, Fogel, and Michalewicz 2000a,b; Cole”
• The application of artificial neural networks to the analysis of remotely sensed data (2008, methodology): “GAs (Haupt and Haupt 1998) have been used for the design of optimal ANNs.”
• Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation (2009, methodology): “Representative methodologies in the heuristic classification are the Probabilistic Roadmaps, Rapidly Exploring Random Trees, Neural Networks, Genetic Algorithms [1,7,11], Simulated Annealing, Ant Colony Optimization, Particle Swarm Optimizer [3,6], Stigmergy, Wavelets, Tabu Search, and Fuzzy Logic [”
• Minimum-Energy Point-to-Point Trajectory Planning for a Motor-Toggle Servomechanism (2012, methodology): “In this paper, the reproduction procedure adopts the roulette wheel selection, and the crossover and uniform mutation adopt the methods in [21].”
• Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification (2018, background): “In principle, a desirable population should contain not only good but also the relatively bad ones for enhancing the diversity [54], [55].”
• Thermoeconomic assessment and multi objective optimization of a solar micro CCHP based on Organic Rankine Cycle for domestic application (2015, background): “add them together to obtain a single objective function which can be maximized or minimized using GA [49].”