A tabu search-based algorithm for the fuzzy clustering problem

Khaled S. Al-Sultan; Chawki A. Fedjki

doi:10.1016/S0031-3203(97)00020-4

A tabu search-based algorithm for the fuzzy clustering problem

Khaled S. Al-Sultan^*, Chawki A. Fedjki

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Contribution to journal › Article › peer-review

62 Scopus citations

Abstract

The Fuzzy Clustering Problem (FCP) is a mathematical program which is difficult to solve since it is nonconvex, which implies possession of many local minima. The fuzzy C-means heuristic is the widely known approach to this problem, but it is guaranteed only to yield local minima. In this paper, we propose a new approach to this problem which is based on tabu search technique, and aims at finding a global solution of FCP. We compare the performance of the algorithm with the fuzzy C-means algorithm.

Original language	English
Pages (from-to)	2023-2030
Number of pages	8
Journal	Pattern Recognition
Volume	30
Issue number	12
DOIs	https://doi.org/10.1016/S0031-3203(97)00020-4
State	Published - Dec 1997

Keywords

Fuzzy C-means algorithm
Fuzzy clustering
Global optimization
Tabu search technique

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

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10.1016/S0031-3203(97)00020-4

Cite this

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title = "A tabu search-based algorithm for the fuzzy clustering problem",

abstract = "The Fuzzy Clustering Problem (FCP) is a mathematical program which is difficult to solve since it is nonconvex, which implies possession of many local minima. The fuzzy C-means heuristic is the widely known approach to this problem, but it is guaranteed only to yield local minima. In this paper, we propose a new approach to this problem which is based on tabu search technique, and aims at finding a global solution of FCP. We compare the performance of the algorithm with the fuzzy C-means algorithm.",

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AU - Fedjki, Chawki A.

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AB - The Fuzzy Clustering Problem (FCP) is a mathematical program which is difficult to solve since it is nonconvex, which implies possession of many local minima. The fuzzy C-means heuristic is the widely known approach to this problem, but it is guaranteed only to yield local minima. In this paper, we propose a new approach to this problem which is based on tabu search technique, and aims at finding a global solution of FCP. We compare the performance of the algorithm with the fuzzy C-means algorithm.

KW - Fuzzy C-means algorithm

KW - Fuzzy clustering

KW - Global optimization

KW - Tabu search technique

UR - https://www.scopus.com/pages/publications/0031353193

U2 - 10.1016/S0031-3203(97)00020-4

DO - 10.1016/S0031-3203(97)00020-4

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EP - 2030

JO - Pattern Recognition

JF - Pattern Recognition

IS - 12

ER -

A tabu search-based algorithm for the fuzzy clustering problem

Abstract

Keywords

ASJC Scopus subject areas

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