Meta-optimization of bio-inspired algorithms for antenna array design

Virgilio Zúñiga-Grajeda; Alberto Coronado-Mendoza; Kelly Joel Gurubel-Tun

Displaying similar documents to “Meta-optimization of bio-inspired algorithms for antenna array design”

A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems

Sotirios K. Goudos (2016)

Open Mathematics

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A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization...

On approximating NP-hard optimization problems.

Håstad, Johan (1998)

Documenta Mathematica

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High-performance simulation-based algorithms for an alpine ski racer's trajectory optimization in heterogeneous computer systems

Roman Dębski (2014)

International Journal of Applied Mathematics and Computer Science

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Effective, simulation-based trajectory optimization algorithms adapted to heterogeneous computers are studied with reference to the problem taken from alpine ski racing (the presented solution is probably the most general one published so far). The key idea behind these algorithms is to use a grid-based discretization scheme to transform the continuous optimization problem into a search problem over a specially constructed finite graph, and then to apply dynamic programming to find an...

Ant Colony Optimisation: models and applications.

Oscar Cordón, Francisco Herrera, Thomas Stützle (2002)

Mathware and Soft Computing

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Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the shortest path searching behavior of various ant species [1,2]. The initial work of Dorigo, Maniezzo and Colorni [3,4] who proposed the first ACO algorithm called Ant System, has stimulated a still strongly increasing number of researchers to develop more sophisticated and better performing ACO algorithms that are used to successfully solve a large number of hard combinatorial optimization problems such as the traveling...