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2008 32nd Annual IEEE International Computer Software and Applications Conference
Swarm Intelligence in the Optimization of Software Development Project Schedule
July 28-August 01
ISBN: 978-0-7695-3262-2
ASCII Text
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Tad Gonsalves, Atsushi Ito, Ryo Kawabata, Kiyoshi Itoh, "Swarm Intelligence in the Optimization of Software Development Project Schedule," Computer Software and Applications Conference, Annual International, pp. 587-592, 2008 32nd Annual IEEE International Computer Software and Applications Conference, 2008.
 
 
BibTex
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@article{ 10.1109/COMPSAC.2008.179,
author = {Tad Gonsalves and Atsushi Ito and Ryo Kawabata and Kiyoshi Itoh},
title = {Swarm Intelligence in the Optimization of Software Development Project Schedule},
journal ={Computer Software and Applications Conference, Annual International},
volume = {0},
year = {2008},
issn = {0730-3157},
pages = {587-592},
doi = {http://doi.ieeecomputersociety.org/10.1109/COMPSAC.2008.179},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer Software and Applications Conference, Annual International
TI - Swarm Intelligence in the Optimization of Software Development Project Schedule
SN - 0730-3157
SP587
EP592
A1 - Tad Gonsalves,
A1 - Atsushi Ito,
A1 - Ryo Kawabata,
A1 - Kiyoshi Itoh,
PY - 2008
KW - Particle Swarm Optimization
KW - Optimization
KW - Resource-Constrained Multi-Project Scheduling Problem
VL - 0
JA - Computer Software and Applications Conference, Annual International
ER -
 
The Software Development Project Scheduling Problem is similar to the well-known Resource-Constrained Multi-Project Scheduling Problem (RCMPSP). It consists in determining a schedule of tasks taking into consideration resource availabilities and precedence constraints, while optimizing an objective. Like RCMPSP, it is an NP-hard problem. In this paper, a task segmentation scheme to schedule a software development project is proposed and the average duration of the multiple concurrent projects is minimized using the Particle Swarm Optimization (PSO) meta-heuristic. PSO is a recent meta-heuristic algorithm, known for its simplicity in programming and its rapid convergence. A series of experiments show optimum results for several software development schedule scenarios.
Index Terms:
Particle Swarm Optimization, Optimization, Resource-Constrained Multi-Project Scheduling Problem
Citation:
Tad Gonsalves, Atsushi Ito, Ryo Kawabata, Kiyoshi Itoh, "Swarm Intelligence in the Optimization of Software Development Project Schedule," compsac, pp.587-592, 2008 32nd Annual IEEE International Computer Software and Applications Conference, 2008
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