Using Imperialist competitive algorithm optimization in multi-response nonlinear programming

Bashiri, Mahdi; Bagheri, Masoud

Volume 24, Issue 3 (IJIEPR 2013) IJIEPR 2013, 24(3): 229-235 | Back to browse issues page

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Bashiri M, Bagheri M. Using Imperialist competitive algorithm optimization in multi-response nonlinear programming . IJIEPR 2013; 24 (3) :229-235
URL: http://ijiepr.iust.ac.ir/article-1-427-en.html

Using Imperialist competitive algorithm optimization in multi-response nonlinear programming

Mahdi Bashiri

¹, Masoud Bagheri²

1- Shahed University , bashiri.m@gmail.com
2- Shahed University

Abstract: (10169 Views)

The quality of manufactured products is characterized by many controllable quality factors. These factors should be optimized to reach high quality products. In this paper we try to find the controllable factors levels with minimum deviation from the target and with a least variation. To solve the problem a simple aggregation function is used to aggregate the multiple responses functions then an imperialist competitive algorithm is used to find the best level of each controllable variable. Moreover the problem has been better analyzed by Pareto optimal solution to release the aggregation function. Then the proposed multiple response imperialist competitive algorithm (MRICA) has been compared with Multiple objective Genetic Algorithm. The experimental results show efficiency of the proposed approach in both aggregation and non aggregation methods in optimization of the nonlinear multi-response programming.

Keywords: Multi-response Optimization, Imperialist competitive, Genetic Algorithm, Response surface methodology

Full-Text [PDF 346 kb] (3327 Downloads)

Type of Study: Research | Subject: Optimization Techniques
Received: 2012/05/5 | Accepted: 2013/09/28 | Published: 2013/09/28