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

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


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.


Software cost estimation Analogy based estimation Genetic algorithm Multi-criteria decision making Nonlinear integer programming 


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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of CSEBIT, MesraRanchiIndia

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