Title : ( A Fish School Clustering Algorithm: Applied to Student Sectioning Problem )
Authors: Mahmood Amintoosi , Mahmood Fathy , Nasser Mozayani , A.T. Rahmani ,
Full TextAbstract
In this paper a new clustering algorithm based on the fish school behavior is proposed. The algorithm is an extension of the classical flock model of Reynolds with a new characteristic. We have different kinds of fishes: leader fish and follower fish. In addition it is supposed that our artificial fishes live in some predefined caves. The school is a set of groups, which every group has a leader and lie in a cave in every time. Other members of the group are leader followers. Regarding the concepts of joining and splitting of the groups, a clustering algorithm which is almost similar to hierarchical clustering algorithms is proposed. The proposed algorithm is applied to student sectioning problem, a sub problem of timetabling problem. Simulation results show the applicability of the proposed algorithm.
Keywords
, Artificial life, Fish School, Flock, Clustering, Student sectioning, educational timetabling, fuzzy evaluation
@inproceedings{paperid:1106571,
author = {Amintoosi, Mahmood and محمود فتحی and ناصر مزینی and عادل ترکمان رحمانی},
title = {A Fish School Clustering Algorithm: Applied to Student Sectioning Problem},
booktitle = {LSMS2007, Life System Modeling and Simulation 2007},
year = {2007},
location = {شانگهای},
keywords = {Artificial life; Fish School; Flock; Clustering;
Student sectioning; educational timetabling; fuzzy evaluation},
}
%0 Conference Proceedings
%T A Fish School Clustering Algorithm: Applied to Student Sectioning Problem
%A Amintoosi, Mahmood
%A محمود فتحی
%A ناصر مزینی
%A عادل ترکمان رحمانی
%J LSMS2007, Life System Modeling and Simulation 2007
%D 2007
