Clustering analysis of railway driving missions with niching
ISSN: 0332-1649
Article publication date: 4 May 2012
Abstract
Purpose
A wide number of applications requires classifying or grouping data into a set of categories or clusters. The most popular clustering techniques to achieve this objective are K‐means clustering and hierarchical clustering. However, both of these methods necessitate the a priori setting of the cluster number. The purpose of this paper is to present a clustering method based on the use of a niching genetic algorithm to overcome this problem.
Design/methodology/approach
The proposed approach aims at finding the best compromise between the inter‐cluster distance maximization and the intra‐cluster distance minimization through the silhouette index optimization. It is capable of investigating in parallel multiple cluster configurations without requiring any assumption about the cluster number.
Findings
The effectiveness of the proposed approach is demonstrated on 2D benchmarks with non‐overlapping and overlapping clusters.
Originality/value
The proposed approach is also applied to the clustering analysis of railway driving profiles in the context of hybrid supply design. Such a method can help designers to identify different system configurations in compliance with the corresponding clusters: it may guide suppliers towards “market segmentation”, not only fulfilling economic constraints but also technical design objectives.
Keywords
Citation
Jaafar, A., Sareni, B. and Roboam, X. (2012), "Clustering analysis of railway driving missions with niching", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 31 No. 3, pp. 920-931. https://doi.org/10.1108/03321641211209807
Publisher
:Emerald Group Publishing Limited
Copyright © 2012, Emerald Group Publishing Limited