Forecasting enterprise resource planning software effort using evolutionary support vector machine inference model

• Published in: International journal of project management Vol. 30; no. 8; pp. 967 - 977
• Main Authors: Chou, Jui-Sheng, Cheng, Min-Yuan, Wu, Yu-Wei, Wu, Cheng-Chieh
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.11.2012; Elsevier Science Ltd
• Subjects: Computer programs; Enterprise resource planning; Evolutionary; Genetic algorithms; Hybrid intelligence; Inference; Mathematical models; Project management; Software; Software effort prediction; Statistical inference; Studies; Support vector machines; Systems development; Software effort prediction; Enterprise resource planning; Project management; Hybrid intelligence
• ISSN: 0263-7863; 1873-4634
• DOI: 10.1016/j.ijproman.2012.02.003

Despite significant advances in procedures that facilitate project management, the continued reliance of software managers on guesswork and subjective judgment causes frequent project time overruns. This study uses an Evolutionary Support Vector Machine Inference Model (ESIM) for efficiently and accurately estimating the person-hour of ERP system development projects. The proposed ESIM is a hybrid intelligence model integrating a support vector machine (SVM) with a fast messy genetic algorithm (fmGA). The SVM mainly provides learning and curve fitting while the fmGA minimizes errors. The analytical results in this study confirm that, compared to artificial neural networks and SVM, the proposed ESIM provides preliminary prediction at early phase of ERP software development effort for the manufacturing firms with superior accuracy, shorter training time and less overfitting. Future research can develop user-friendly expert systems with window or browser interfaces that can be used by planning personnel to flexibly input related variables and to estimate development effort and corresponding project time/cost. ► This study uses an Evolutionary Support Vector Machine Inference Model (ESIM) for estimating the person-hour of Enterprise Resource Planning (ERP) projects. ► The ESIM is a hybrid intelligence model integrating a support vector machine with a fast messy genetic algorithm. ► The ESIM provides preliminary prediction of ERP software development effort with superior accuracy. ► Future research can develop user-friendly expert systems to estimate development effort.