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Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem

by Sarah E. Almshhadany, Laheeb M. Ibrahim
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 16
Year of Publication: 2018
Authors: Sarah E. Almshhadany, Laheeb M. Ibrahim
10.5120/ijca2018917753

Sarah E. Almshhadany, Laheeb M. Ibrahim . Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem. International Journal of Computer Applications. 181, 16 ( Sep 2018), 6-13. DOI=10.5120/ijca2018917753

@article{ 10.5120/ijca2018917753,
author = { Sarah E. Almshhadany, Laheeb M. Ibrahim },
title = { Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2018 },
volume = { 181 },
number = { 16 },
month = { Sep },
year = { 2018 },
issn = { 0975-8887 },
pages = { 6-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number16/29904-2018917753/ },
doi = { 10.5120/ijca2018917753 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:39.299109+05:30
%A Sarah E. Almshhadany
%A Laheeb M. Ibrahim
%T Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 16
%P 6-13
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a new multi-objective artificial fish swarm algorithm was proposed based on the principles of PAES algorithm and it is used to solve SPSP. The aim of this proposal is to solve the software project scheduling problem with artificial fish swarm algorithm and to overcome some disadvantages that AFSA suffer from. The performance of the proposed algorithm was compared with another multi-objective AFSA based on the use of global information (GAFSA), in terms of speed, quality of produced solutions and complexity of algorithm operations. The results show that the proposed algorithm is faster, easier to implement, require less computations, and had obtained better nondominated solutions than the other algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Software project scheduling problem multi-objective optimization artificial fish swarm algorithm.

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