Genetic Algorithms: Advances in Research and Applications


Julia Carson (Editor)

Series: Computer Science, Technology and Applications
BISAC: COM014000

In Chapter One, a revision and complementary analysis of three interesting cases where stochastic strategies are applied to get the optimal design of intensified schemes is presented. The revisited cases include multicomponent, extractive and reactive thermally coupled distillation. Chapter Two performs parameter optimization on a genetic algorithm to skip the tuning parameter process during unmanned aerial vehicle path planning. Results show that truncation selection at 20% is highly recommended for genetic algorithm path planning application because of its low average path and computational costs.

Chapter 3 describes the calibration of the numerical model of the Monte da Virgem telecommunications tower, located near the city of Porto, Portugal. The calibration of the numerical model of the tower relies on the application of an iterative method based on a genetic algorithm. Chapter 4 describes the genetic algorithm-based calibration procedure for a microscopic traffic simulation model, focusing on freeways and modern roundabouts. For both case studies, the genetic algorithm tool in MATLAB® was applied in order to reach the convergence between the outputs from Aimsun microscopic simulator and the observed data. (Imprint: Nova)


Table of Contents


Chapter 1. Genetic Algorithms: A Tool for Optimizing Intensified Distillation Sequences
Fernando Israel Gómez-Castro, Claudia Gutiérrez-Antonio, Abel Briones-Ramírez and Juan Gabriel Segovia-Hernández (Department of Chemical Engineering, Division of Natural and Exact Sciences, Campus Guanajuato, University of Guanajuato, Guanajuato, México, and others)

Chapter 2. The Optimization of a Genetic Algorithm for Unmanned Aerial Vehicle Path Planning
Parvathy Rajendran and Kai Yit Kok (School of Aerospace Engineering, University of Science, Malaysia, Nibong Tebal, Pulau Pinang, Malaysia)

Chapter 3. Calibration of the Numerical Model of a Telecommunications Tower Based on Genetic Algorithms
Diogo Ribeiro, Jorge Leite, Rafael de Pauli, Vinicius Alves, Bruno Costa and Rui Calçada (CONSTRUCT-LESE, School of Engineering, Polytechnic of Porto, Porto, Portugal, and others)

Chapter 4. Application of a Genetic Algorithm in Calibration of Traffic Microsimulation Models
Orazio Giuffrè, Anna Granà, Raffaele Mauro, Antonino Sferlazza and Maria Luisa Tumminello (University of Palermo, Palermo, Italy)


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