Title: Uncertain multi-objective programming model: a genetic algorithm approach
Authors: Kailash Lachhwani
Addresses: Department of Applied Sciences, National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh – 160 019, India; Department of Mathematics, Government Engineering College, Bikaner (Rajasthan) – 334 004, India
Abstract: This paper aims at describing an uncertain multi-objective programming model involving uncertain variables with genetic algorithm approach. In this paper, the uncertain multiobjective programming model is converted into an equivalent crisp mathematical programming model. Then, a genetic algorithm is proposed to search the Stackelberg-Nash equilibrium of the uncertain multiobjective programming model with supporting numerical illustrations. Finally, sensitivity analysis study is carried out over parameters of algorithm and solution obtained to show efficiency and robustness of genetic algorithm for uncertain multiobjective programming model.
Keywords: uncertain multi-objective programming; genetic algorithm; Stackelberg-Nash equilibrium; expected value; crisp model; uncertain measure.
DOI: 10.1504/IJMOR.2017.086304
International Journal of Mathematics in Operational Research, 2017 Vol.11 No.2, pp.271 - 283
Received: 15 Aug 2015
Accepted: 18 Feb 2016
Published online: 04 Sep 2017 *