DocumentCode
1995158
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
fYear
2013
fDate
20-24 May 2013
Firstpage
405
Lastpage
414
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/IPDPSW.2013.212
Filename
6650913
Link To Document