Title
An artificial fish swarm optimization algorithm to solve set covering problem
Date Issued
01 January 2016
Access level
metadata only access
Resource Type
conference paper
Author(s)
Crawford B.
Olguín E.
Villablanca S.
Rubio Á.
Jaramillo A.
Salas J.
Publisher(s)
Springer Verlag
Abstract
The Set Covering Problem (SCP) consists in finding a set of solutions that allow to cover a set of necessities with the minor possible cost. There are many applications of this problem such as rolling production lines or installation of certain services like hospitals. SCP has been solved before with different algorithms like genetic algorithm, cultural algorithm or firefly algorithm among others. The objective of this paper is to show the performance of an Artificial Fish Swarm Algorithm (AFSA) in order to solve SCP. This algorithm, simulates the behavior of a fish shoal inside water and it uses a population of points in space to represent the position of a fish in the shoal. Here we show a study of its simplified version of AFSA in a binary domain with its modifications applied to SCP. This method was tested on SCP benchmark instances from OR-Library website.
Start page
892
End page
903
Volume
9799
Language
English
OCDE Knowledge area
Matemáticas Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-84978863610
ISBN
9783319420066
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
978-331942006-6
Conference
29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016
Sources of information: Directorio de Producción Científica Scopus