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Multi Objective Particle Swarm Optimization for Software Cost Estimation

by Prasad Reddy P.V.G.D, Hari CH.V.M.K., Srinivasa Rao T.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 3
Year of Publication: 2011
Authors: Prasad Reddy P.V.G.D, Hari CH.V.M.K., Srinivasa Rao T.
10.5120/3884-5437

Prasad Reddy P.V.G.D, Hari CH.V.M.K., Srinivasa Rao T. . Multi Objective Particle Swarm Optimization for Software Cost Estimation. International Journal of Computer Applications. 32, 3 ( October 2011), 13-17. DOI=10.5120/3884-5437

@article{ 10.5120/3884-5437,
author = { Prasad Reddy P.V.G.D, Hari CH.V.M.K., Srinivasa Rao T. },
title = { Multi Objective Particle Swarm Optimization for Software Cost Estimation },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 3 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number3/3884-5437/ },
doi = { 10.5120/3884-5437 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:11.212481+05:30
%A Prasad Reddy P.V.G.D
%A Hari CH.V.M.K.
%A Srinivasa Rao T.
%T Multi Objective Particle Swarm Optimization for Software Cost Estimation
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 3
%P 13-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software Project Management activities are classified as planning, monitoring-control and termination. Planning is the most important activity in project management which defines the resources required to complete the project successfully. Software Cost Estimation is the process of predicting the cost and time required to complete the project. The basic input for the software cost estimation is coding size and set of cost drivers, the output is Effort in terms of Person-Months (PM’s). In this paper we proposed a model for software cost estimation using Multi Objective (MO) Particle Swarm Optimization. The parameters of model tuned by using MOPSO considering two objectives Mean Absolute Relative Error and Prediction. The COCOMO dataset is considered for testing the model. It was observed that the model gives better results when compared with the standard COCOMO model. It is also observed, when provided with enough classification among training data may give better results.

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Index Terms

Computer Science
Information Sciences

Keywords

KDLOC-thousands of delivered lines of code PM- person months PSO- particle swarm optimization COCOMO- constructive cost estimation MO- Multi Objective

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