Search
3 articles for “types of TLBO”
-
Survey on Teaching-Learning-Based Optimization
Abstract: Optimization is a process for finding maximum or minimum of a function subject to set of functions. In other words optimization finds the most suitable value for a function within a given domain. Global Optimization means finding minimum value of all local minima and maxima value from all local maxima. The procedure to find out the global maxima or minima point is called a Global Optimization. Teaching-Learning-Based Optimization(TLBO) is recently …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 3, Issue 1, 2016 · pp. 7–15 Read article
-
Comparative Performance Analysis of Swarm and Intelligent Evolutionary Techniques for Optimal Design of Distribution Transformer
Abstract: This paper addresses the method of optimal design of a three phase distribution transformer using Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Teaching-Learning-Based-Optimization Algorithm (TLBO). The design and analysis programs have been developed for constrained optimal design with cost as the objective function. The active part cost of the transformer has been minimized keeping in view BEE (Bureau of Energy Efficiency) standards and constraints. A design example on a …
Published in Trends in Electrical Engineering · Vol. 5, Issue 3, 2015 · pp. 46–58 Read article
-
Salp Swarm Algorithm Optimized Tilt Integral Derivative Controller for Controlling the Frequency of Load in Multi Area Multi Source Power System With and Without Electric Vehicle
Abstract: Abstract- In this paper, Salp Swarm Algorithm (SSA) is used to tune the parameters of tilt integral derivative (TID) controller to control the frequency of load in multi area interconnected multi source system in the presence of electric vehicle (EV). In the proposed system there are two areas and each area consist of three sources i.e. gas unit, hydro unit and reheat thermal unit . In order to exhibit the …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 25–36 Read article