Aspiration level-based non-dominated sorting genetic algorithm-II and III for multi-objective shortest path problem in a trapezoidal environment

Aniket Todkar and Jayesh M. Dhodiya

International Journal of Mathematics in Operational Research, 2024, vol. 27, issue 2, 223-253

Abstract: The present article provides aspiration level (AL)-based non-dominated sorting genetic algorithm (NSGA)-II and AL-based NSGA-III utilising an exponential membership function (EMF) with possibility distribution to tackle fuzzy multi-objective shortest path problem (FMOSPP). In this study, fuzzy judgement for trapezoidal fuzzy number is classified for the decision-maker (DM) to optimise fuzzy objective function scenarios like optimistic, most likely lower, most likely upper, and pessimistic at the same time, utilising α-level sets. A numerical demonstration and a dataset have been offered to portray the application of the recommended methodologies. This study suggests that AL-based NSGA-II and AL-based NSGA-III can handle FMOSPP effectively and efficiently with optimal outputs. These methods provide solutions as per DM's AL. Thus it is very effective to manage real-world multi-objective shortest path problems (MOSPPs).

Keywords: multi-objective shortest path problem; MOSPP; aspiration level; exponential membership function; EMF; α -level set; trapezoidal fuzzy number; genetic algorithm. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=137054 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:27:y:2024:i:2:p:223-253

Access Statistics for this article

More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().