Title :
A Possibilistic Framework for Solving Multi-objective Problems under Uncertainty: Definition of New Pareto Optimality
Author :
Oumayma, Bahri ; Nahla, Ben Amor ; Talbi, El-Ghazali
Author_Institution :
LARODEC, Univ. de Tunis, Tunis, Tunisia
Abstract :
This paper deals with multi-objective problems under uncertainty, using the possibilistic framework which offers a simple and natural way to express uncertainty underlying most of real-world problems. To this end, we propose new Pareto relations for ranking the generated triangular fuzzy solutions in both mono-objective and multi-objective cases. The proposed method is applied to solve a multi-objective Vehicle Routing Problem (VRP) with uncertain demands.
Keywords :
Pareto optimisation; fuzzy set theory; transportation; Pareto relations; VRP; generated triangular fuzzy solutions; monoobjective case; multiobjective case; multiobjective problems solution; multiobjective vehicle routing problem; possibilistic framework; Pareto optimization; Possibility theory; Routing; Uncertainty; Vectors; Vehicles; Multi-objective optimization; Pareto relations; Possibilistic framework; Triangular fuzzy numbers; Uncertainty; VRP;
Conference_Titel :
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2013 IEEE 27th International
Conference_Location :
Cambridge, MA
Print_ISBN :
978-0-7695-4979-8
DOI :
10.1109/IPDPSW.2013.212
