Title: Utilisation of pruned Pareto-optimal solutions in the multi objective optimisation: an application to system redundancy allocation problems
Authors: Asghar Moeini; Mehdi Foumani; Kouroush Jenab
Addresses: School of Computer Science, Engineering and Mathematics, Flinders University, Bedford Park 34, Adelaide, Australia ' School of Applied Sciences and Engineering, Monash University, Gippsland Campus, Churchill, VIC 3842, Australia ' Society of Reliability Engineering-Ottawa, 812-761 Bay Street, Toronto, Ontario, Canada
Abstract: Multi-objective optimisation problems normally have not one but a set of solutions, which are called Pareto-optimal solutions or non-dominated solutions. Once a Pareto-optimal set has been obtained, the decision-maker faces the challenge of analysing a potentially large set of solutions. Selecting one solution over others can be quite a challenging task because the Pareto set can contain an unmanageable number of solutions. This process is called post-Pareto optimality analysis. To deal with this difficulty, this study proposes the approach that promisingly prunes the Pareto optimal set. In this study, the newly developed approach uses Monte-Carlo simulation taking into account the decision maker's prioritisation to prune the Pareto optimal set. Then, the central weight vector, the optimal frequently appearance index and upper and lower bands of weights are enclosed to each solution to facilitate selecting a final solution. The well-known redundancy allocation problem is used to show the performance of the proposed method.
Keywords: multi-objective optimisation; post-Pareto optimality analysis; reliability optimisation; system redundancy allocation; Monte Carlo simulation.
International Journal of Applied Decision Sciences, 2013 Vol.6 No.1, pp.50 - 65
Published online: 28 Nov 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article