About this Journal Submit a Manuscript Table of Contents
Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 652391, 13 pages
http://dx.doi.org/10.1155/2012/652391
Research Article

Multiobjective Optimization of Irreversible Thermal Engine Using Mutable Smart Bee Algorithm

Department of Mechanical Engineering, Babol University of Technology, P.O. Box 484, Babol, Iran

Received 13 July 2011; Revised 6 October 2011; Accepted 14 November 2011

Academic Editor: Chuan-Kang Ting

Copyright © 2012 M. Gorji-Bandpy and A. Mozaffari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A new method called mutable smart bee (MSB) algorithm proposed for cooperative optimizing of the maximum power output (MPO) and minimum entropy generation (MEG) of an Atkinson cycle as a multiobjective, multi-modal mechanical problem. This method utilizes mutable smart bee instead of classical bees. The results have been checked with some of the most common optimizing algorithms like Karaboga’s original artificial bee colony, bees algorithm (BA), improved particle swarm optimization (IPSO), Lukasik firefly algorithm (LFFA), and self-adaptive penalty function genetic algorithm (SAPF-GA). According to obtained results, it can be concluded that Mutable Smart Bee (MSB) is capable to maintain its historical memory for the location and quality of food sources and also a little chance of mutation is considered for this bee. These features were found as strong elements for mining data in constraint areas and the results will prove this claim.