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De Rainville, F., Gagné, C., Teytaud, O. and Laurendeau, D. (2009) Optimizing Low-Discrepancy Sequences with an Evolutionary Algorithm. Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, Canada, 8-12 July 2009, 1491-1498.
https://doi.org/10.1145/1569901.1570101

has been cited by the following article:

• TITLE: Six-Element Yagi-Uda Array: An Example of Using Negative Gravity in Central Force Optimization for Improving Decision Space Exploration

  AUTHORS: Richard A. Formato

  KEYWORDS: Central Force Optimization, CFO, Optimization, Antenna Design and Optimization, Evolutionary Algorithm, Swarm Algorithm, Metaheuristic, Yagi, Yagi-Uda, Negative Gravity

  JOURNAL NAME: Wireless Engineering and Technology, Vol.16 No.1, January 31, 2025

  ABSTRACT: State-of-the-art antenna design and optimization (D/O) is increasingly being done using Global Search and Optimization (GSO) algorithms such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Differential Evolution (DE), and a plethora of other evolutionary algorithms, among them Central Force Optimization (CFO), which is the subject of this note. CFO analogizes real gravity in the real Universe so that its gravity is usually attractive in nature, that is, “positive”. But in metaphorical CFO space the algorithm designer is free to turn gravity on its head by making it negative, and doing so to a small extent can improve CFO’s exploration of the search space thus providing even better results. This extension is discussed in some detail and applied to a 6-element Yagi-Uda array as an example.