Application of Teaching Learning Based Optimization in antenna designing

Y Kosta,V Mishra,S Dwivedi

doi:10.7716/aem.v4i1.255

Abstract

Numerous optimization techniques are studied and applied on antenna designs to optimize various performance parameters. Authors used many Multiple Attributes Decision Making (MADM) methods, which include, Weighted Sum Method (WSM), Weighted Product Method (WPM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytic Hierarchy Process (AHP), ELECTRE, etc. Of these many MADM methods, TOPSIS and AHP are more widely used decision making methods. Both TOPSIS and AHP are logical decision making approaches and deal with the problem of choosing an alternative from a set of alternatives which are characterized in terms of some attributes. Analytic Hierarchy Process (AHP) is explained in detail and compared with WSM and WPM. Authors ﬁ- nally used Teaching-Learning-Based Optimization (TLBO) technique; which is a novel method for constrained antenna design optimization problems.

Highlights

Multiple Criterion Decision Making (MCDM) refers to making decisions from multiple conflicting criteria
MCDM is broadly classified into two categories: multiple attribute decision making (MADM) and multiple objective decision making (MODM)
Teaching Learning Based Optimization(TLBO) method is a kind of MODM technique

Summary

Introduction

Multiple Criterion Decision Making (MCDM) refers to making decisions from multiple conflicting criteria. MCDM is broadly classified into two categories: multiple attribute decision making (MADM) and multiple objective decision making (MODM). MODM methods have decision variable values with a large number of choices and select the best that should satisfy the decision maker’s constraints and preference priorities. MADM is an approach employed to solve problems involving selection from among a finite number of alternatives. Each decision table (or decision matrix) in MADM methods has four main parts, namely: (a) alternatives, (b) attributes, (c) weight , and (d) measures of performance of alternatives w.r.t. the attributes. M), weights of attributes, wj (for j=1, 2, .., M) and the measures of performance of alternatives, mij (for i= 1, 2, .., N; j=1, 2, .., M) [1]

MADM Methods

Teaching Learning Based Optimization in Antenna Designing

Design and simulation

Applications of radome structure

Conclusion