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2007-2008 Faculty Lecture Series in Electrical Engineering
Spring 2008

Nature Inspired Optimization Techniques in Engineering: Let Darwin and the bees help improve your designs
Professor Yahya Rahmat-Samii
UCLA Electrical Engineering

Wednesday, May 21, 2008 at 1:00PM

54-134 Engineering IV Building
Refreshments Served

Abstract: Engineers are constantly challenged with the temptation to search for optimum solutions for complex engineering system designs. The ever increasing advances in computational power have fueled this temptation. The well-known brute force design methodologies are systematically being replaced by the state-of-the-art Evolutionary Optimization (EO) techniques. In recent years, EO techniques are finding growing applications to the design of all kind of systems with increasing complexity. Among various EO's, nature inspired techniques such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) have attracted considerable attention. GA utilizes an optimization methodology which allows a global search of the cost surface via the mechanism of the statistical random processes dictated by the Darwinian evolutionary concept (adaptation, selection, survivability and mutation). PSO is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms of bees looking for the most fertile feeding location applying their cognitive and social knowledge. This presentation will focus on: (a) an engineering introduction to GA and PSO by describing in a unique fashion the underlying concepts and recent advances for those who have used these techniques and for those who have not had any experiences in these areas, (b) demonstration of the potential applications of GAs and PSO's to a variety of engineering designs including antennas for remote sensing and satellite communication applications, arrays for radio astronomy imaging, multi-band, wideband and UWB antenna designs in personal communications, design of electromagnetic and photonic bandgap (EBG & PBG) structures, etc, and (c) assessment of the advantages and the limitations of these techniques.

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