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A Genetic Algorithm Approach for Multi-criteria Project Selection for Analogy-Based Software Cost Estimation

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Computational Intelligence in Data Mining - Volume 3

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 33))

Abstract

This paper presents genetic algorithms as multi-criteria project selection for improving the Analogy Based Estimation (ABE) process, which is suitable to reuse past project experience to create estimation of the new projects. An attempt has also been made to create a multi-criteria project selection problem with and without allowing for interactive effects between projects based on criteria which are determined by the decision makers. Two categories of projects are also presented for comparison purposes with other traditional optimization methods and the experimented results show the capability of the proposed Genetic Algorithm based method in multi-criteria project selection problem and it can be used as an efficient solution to the problem that will enhance the ABE process. Here, Mean Absolute Relative Error (MARE) is used to evaluate the performance of ABE process and it has been found that interactive effects between projects may change the results.

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Authors and Affiliations

  1. Department of CSE, BIT, Mesra, Ranchi, India

    Sweta Kumari & Shashank Pushkar

Authors
  1. Sweta Kumari
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  2. Shashank Pushkar
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Corresponding author

Correspondence to Sweta Kumari .

Editor information

Editors and Affiliations

  1. School of Electrical and Information Engineering, University of South Australia, South Australia, Australia

    Lakhmi C. Jain

  2. Computer Science and Engineering, Veer Surendra Sai University of Technolo, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Eng., National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Kumari, S., Pushkar, S. (2015). A Genetic Algorithm Approach for Multi-criteria Project Selection for Analogy-Based Software Cost Estimation. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 3. Smart Innovation, Systems and Technologies, vol 33. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2202-6_2

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  • DOI: https://doi.org/10.1007/978-81-322-2202-6_2

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2201-9

  • Online ISBN: 978-81-322-2202-6

  • eBook Packages: EngineeringEngineering (R0)

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