Group Search Optimization with Multi Objective Thermal Power Dispatch - An Overview
Abstract
A group search optimizer (GSO) algorithm to solve the highly constrained multi objective power dispatch (MOPD) problem with conflicting and competing objective. The algorithm employs a stochastic learning based interaction and among multi-groups for cooperative search. The two enhancements namely space reduction and chaotic sequence dispersion is to be used in the convergence process. This study reports a group search optimizer (GSO) which is inspired by animal behavior, especially animal searching behavior. The framework is mainly based on the producerscrounger (PS) model. The GSO algorithm is to developed for the solution of standard IEEE 30- bus, 6- generator test system.