Tuning the fuzzy logic system by two meta-heuristics: case study of airline market share on long-haul routes

The paper deals with the application of two meta-heuristics for fine tuning of fuzzy logic model. Two meta-heuristics are used to determine the final set of fuzzy rules and the domain of membership functions for airline market share model. The model aims at determining the airline market share on lo...

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Bibliographic Details
Published in:Transportation research procedia (Online) 2021, Vol.52, p.453-460
Main Authors: Mijović, Nemanja, Kalić, Milica, Kuljanin, Jovana
Format: Article
Language:English
Subjects:
Airline market share
Bee Colony Optimization
Fuzzy-logic system
Particle Swarm Optimization
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Summary:The paper deals with the application of two meta-heuristics for fine tuning of fuzzy logic model. Two meta-heuristics are used to determine the final set of fuzzy rules and the domain of membership functions for airline market share model. The model aims at determining the airline market share on long-haul routes originating from London airport system. For this purpose, the real data was used encompassing several long-haul routes that are characterized by competition between full-service carriers (FSCs) and at least, one low-cost carrier (LCC). The results show that the application of these two meta-heuristics can significantly contribute to improvement in the overall model performance.
ISSN:2352-1465
2352-1465
DOI:10.1016/j.trpro.2021.01.053