A study of genetic algorithm for project selection for analogy based software cost estimation

Y. F. Li; M. Xie; T. N. Goh

doi:10.1109/IEEM.2007.4419393

A study of genetic algorithm for project selection for analogy based software cost estimation

Y. F. Li
, M. Xie
, T. N. Goh

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

25 Citations (Scopus)

Abstract

Software cost estimation is critical for software project management Many approaches have been proposed to estimate the cost with current project by referring to the data collected form past projects. Analogy Based Estimation (ABE), which is essentially a case-based reasoning (CBR) approach, is one of such techniques. In order to achieve successful results from ABE, many previous studies proposed effective methods to optimize the weights of the features (Feature Weighting). However, ABE is still criticized for the low prediction accuracy, and the sensitivity to the outliers. To alleviate these drawbacks, we introduce the selection of appropriate project subsets (Project Selection) by Genetic Algorithm. The promising results of the proposed method and the comparisons against other ABE model and machine learning techniques indicate our method's effectiveness and potential as a candidate method for Software Cost Estimation. © 2007 IEEE.

Original language	English
Title of host publication	IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management
Pages	1256-1260
DOIs	https://doi.org/10.1109/IEEM.2007.4419393
Publication status	Published - 2007
Externally published	Yes
Event	2007 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM 2007) - , Singapore Duration: 2 Dec 2007 → 5 Dec 2007 http://www.ieem.org/public.asp?page=archive.htm http://www.ieem.org/archive/IEEM2007%20Program%20Book.pdf

Conference

Conference	2007 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM 2007)
Place	Singapore
Period	2/12/07 → 5/12/07
Internet address	http://www.ieem.org/public.asp?page=archive.htm http://www.ieem.org/archive/IEEM2007%20Program%20Book.pdf

Research Keywords

Analogy based estimation
Genetic algorithm
Project selection
Software cost estimation

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10.1109/IEEM.2007.4419393

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title = "A study of genetic algorithm for project selection for analogy based software cost estimation",

abstract = "Software cost estimation is critical for software project management Many approaches have been proposed to estimate the cost with current project by referring to the data collected form past projects. Analogy Based Estimation (ABE), which is essentially a case-based reasoning (CBR) approach, is one of such techniques. In order to achieve successful results from ABE, many previous studies proposed effective methods to optimize the weights of the features (Feature Weighting). However, ABE is still criticized for the low prediction accuracy, and the sensitivity to the outliers. To alleviate these drawbacks, we introduce the selection of appropriate project subsets (Project Selection) by Genetic Algorithm. The promising results of the proposed method and the comparisons against other ABE model and machine learning techniques indicate our method's effectiveness and potential as a candidate method for Software Cost Estimation. {\textcopyright} 2007 IEEE.",

keywords = "Analogy based estimation, Genetic algorithm, Project selection, Software cost estimation",

author = "Li, \{Y. F.\} and M. Xie and Goh, \{T. N.\}",

year = "2007",

doi = "10.1109/IEEM.2007.4419393",

language = "English",

isbn = "1424415292",

pages = "1256--1260",

booktitle = "IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management",

note = "2007 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM 2007) ; Conference date: 02-12-2007 Through 05-12-2007",

url = "http://www.ieem.org/public.asp?page=archive.htm, http://www.ieem.org/archive/IEEM2007\%20Program\%20Book.pdf",

}

Li, YF, Xie, M & Goh, TN 2007, A study of genetic algorithm for project selection for analogy based software cost estimation. in IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management., 4419393, pp. 1256-1260, 2007 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM 2007), Singapore, 2/12/07. https://doi.org/10.1109/IEEM.2007.4419393

A study of genetic algorithm for project selection for analogy based software cost estimation. / Li, Y. F.; Xie, M.; Goh, T. N.
IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management. 2007. p. 1256-1260 4419393.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A study of genetic algorithm for project selection for analogy based software cost estimation

AU - Li, Y. F.

AU - Xie, M.

AU - Goh, T. N.

PY - 2007

Y1 - 2007

N2 - Software cost estimation is critical for software project management Many approaches have been proposed to estimate the cost with current project by referring to the data collected form past projects. Analogy Based Estimation (ABE), which is essentially a case-based reasoning (CBR) approach, is one of such techniques. In order to achieve successful results from ABE, many previous studies proposed effective methods to optimize the weights of the features (Feature Weighting). However, ABE is still criticized for the low prediction accuracy, and the sensitivity to the outliers. To alleviate these drawbacks, we introduce the selection of appropriate project subsets (Project Selection) by Genetic Algorithm. The promising results of the proposed method and the comparisons against other ABE model and machine learning techniques indicate our method's effectiveness and potential as a candidate method for Software Cost Estimation. © 2007 IEEE.

AB - Software cost estimation is critical for software project management Many approaches have been proposed to estimate the cost with current project by referring to the data collected form past projects. Analogy Based Estimation (ABE), which is essentially a case-based reasoning (CBR) approach, is one of such techniques. In order to achieve successful results from ABE, many previous studies proposed effective methods to optimize the weights of the features (Feature Weighting). However, ABE is still criticized for the low prediction accuracy, and the sensitivity to the outliers. To alleviate these drawbacks, we introduce the selection of appropriate project subsets (Project Selection) by Genetic Algorithm. The promising results of the proposed method and the comparisons against other ABE model and machine learning techniques indicate our method's effectiveness and potential as a candidate method for Software Cost Estimation. © 2007 IEEE.

KW - Analogy based estimation

KW - Genetic algorithm

KW - Project selection

KW - Software cost estimation

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DO - 10.1109/IEEM.2007.4419393

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SN - 1424415292

SN - 9781424415298

SP - 1256

EP - 1260

BT - IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management

T2 - 2007 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM 2007)

Y2 - 2 December 2007 through 5 December 2007

ER -

A study of genetic algorithm for project selection for analogy based software cost estimation

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