Fuzzy Logic: An Instrument for the Evaluation of Project Status

Authors

  • Radek Doskočil Department of Informatics Brno University of Technology (Czech Republic)

DOI:

https://doi.org/10.46661/revmetodoscuanteconempresa.2213

Keywords:

Project management, earned value management (EVM), soft computing, fuzzy logic, decision-making, gestión de proyectos, gestión del valor ganado (GVG), lógica difusa, toma de decisiones

Abstract

This article considers the use of fuzzy logic to support the evaluation of project status. A brief description of fuzzy set theory, fuzzy logic and the process of calculation is given. The major goal of this paper is to present an expert decision-making fuzzy model for evaluating project status. The model results from the application of the Fuzzy Logic Toolbox. This fuzzy model is based on two basic indices, schedule performance index (SPI) and cost performance index (CPI), of earned value management (EVM). The advantage of the fuzzy model is the ability to transform the input indices SPI and CPI into linguistic variables, as well as linguistic evaluation of overall project status (output). With this approach it is possible to simulate the risk and uncertainty that are always associated with real projects. The scheme of the model, rule block, attributes and their membership functions are mentioned in a case study. The case study contains real data on the development of values of indices SPI and CPI for one project in the field of IT (data file). The analysed project ran from March 2012 to July 2012. The indices SPI and CPI were obtained from control project milestones. There are 5 control milestones in total. The parameters of the model are adjusted on the basis of the data file for each of the variables. The use of fuzzy logic is a particular advantage in decision-making processes where description by algorithms is extremely difficult and criteria are multiplie

Downloads

Download data is not yet available.

References

ACABES, F.; PAJARES, J.; GALÁN, JM., LÓPEZ-PAREDES, A. A new approach for project control under uncertainty. Going back to the basics. International Journal of Project Management. 2014. Vol. 32. No. 3, pp. 423-434.

BERGANTIÑOS, G., VIDAL-PUGA, J. A value for PERT problems, International Game Theory Review. 2009. Vol. 11. No. 4, pp. 419-436.

BUSHAN RAO. P.; SHANKAR. N. Fuzzy Critical Path Method Based on Lexicographic Ordering of Fuzzy Numbers. Pakistan Journal Of Statistics & Operation Research. 2012. Vol. 8. No 1, pp. 139-154.

CZEMPLIK, A. Application of Earned Value Method to Progress Control of Construction Projects. Procedia Engineering. 2014. Vol 91, pp. 424-428.

DOLEŽAL, J., MÁCHAL, P., LACKO, B. a kol. Projektový management podle IPMA . Praha, Grada, 2009. 512 pp.

DOSKOČIL, R., DOUBRAVSKÝ, K. Critical Path Method based on Fuzzy Numbers: Comparison with Monte Carlo Method. In Creating Global Competitive Economies. Rome, Italy. International Business Information Management Association (IBIMA), 2013, pp. 1402-1411.

DOSKOČIL, R., KŘÍŽ, J., KOCH, M. Fuzzy Logic as a Support of Manager Decision Making. Center for Investigations into Information Sytems. 2009. Vol. 5. No. 2, pp. 1-9.

DOSTÁL, P. Advanced Decision Making in Business and Public Services. Brno, CERM. 2011. 167 pp.

Earned Value Management Terms and Formulas for Project Managers. [online]. 2014 [cit. 2014-07-23]. Available from: http://www.dummies.com/how-to/content/earned-value-management-terms-and-formulas-for-pro.html

CHANAS. S.; ZIELINSKI. P. Critical path analysis in the network with fuzzy activity times. Fuzzy sets and Systems. 2001. Vol. 122. No. 2, pp. 195-204.

CHOU, JS; CHONG, WK. A Web-based Framework of Project Performance and Control System. In 2008 IEEE Conference on Robotics, Automation, and Mechatronics, VOLS 1 and 2. New York, USA, 2008, pp. 97-101.

CHUO, JS; CHEN, HM; HOU, CC; LIN, CW. Visualized EVM system for assessing project performance. Automation in Construction. 2010. Vol. 19. No. 5, pp. 596-607.

International project management association. [Online], 2014 [cit. 2014-08-04]. Available from: http://ipma.ch/

KARPÍŠEK, Z. Přehled základních pojmů teorie fuzzy množin a jejich vlastností . Brno: FSI VUT v Brně, 2009.

KHAMOOSHI, H.; GOLAFSHANI, H. EDM: Earned Duration Management, a new approach to schedule performance management and measurement. International Journal of Project Management. 2014. Vol. 32. No. 6, pp. 1019-1041.

KLIR, G. J., YUAN, B. Fuzzy Sets and Fuzzy Logic, Theory and Applications, New Jersy, USA, Prentice Hall, 1995. 279 pp.

KUCHTA. D. Use of Fuzzy numbers in project risk (criticality) assessment. International Journal of Project Management. 2001. Vol. 19. No. 5, pp. 305–310.

LIPKE, W.; ZWIKAEL, O.; HENDERSON, K.; ANBARI, F. Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes. International Journal of Project Management. 2009. Vol. 27. No. 4, pp. 400-407.

MERTL, J. Aplikace metody EVM na konkrétním projektu. Praha, Vysoká škola ekonomická, Fakulta podnikohospodářská, 2014. 88 pp.

MOSLEMI NAENI, L.; SALEHIPOUR, A. Evaluating fuzzy earned value indices and estimates by applying. Expert Systems with Applications. 2011. Vol. 38. No. 7, pp. 8193-8198.

NAENI, L., M.; SHADROKH, S.; SALEHIPOUR. A. A fuzzy approach for the earned value managemen. International Journal of Project Management. 2011. Vol 29. No. 6, pp. 764-772.

NOORI, S., BAGHERPOUR, M., ZAREEI, A. Applying Fuzzy Control Chart in Earned Value Analysis: A New Application. World Applied Sciences Journal. 2008. Vol. 3. No 4. pp. 684-690.

OLIVEROS. A. V. O.; FAYEK, A. R. Fuzzy Logic Approach for Activity Delay Analysis and Schedule Updating. Journal of Construction Engineering and Management. 2005. Vol. 131. No. 1, pp. 42-51.

PÉREZ, J. G.; RAMBAUD, S. C.; GARCÍA, L. B. G. The two-sided power distribution for the treatment of the uncertainty in PERT, Statistical Methods and Applications. 2005. Vol. 14. No. 2, pp. 209-222.

Project Management Institute. A guide to the project management body of knowledge (PMBOK® guide). 5th edition, 2013.

RAIS, K., SMEJKAL V. Řízení rizik ve firmách a jiných organizacích, Praha, Grada, 2013, 488 pp.

RELICH. M.; MUSZYŃSKI, W. The use of intelligent systems for planning and scheduling of product development projects. 18th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems - KES2014. Gdynia, Poland, 2014, pp. 1586-1595.

ROSENAU, M. Řízení projektů – příklady, teorie, praxe, Brno, Computer Press, 2007. 360 pp.

ROWE, S. F. Earned value management: A global and cross-industry perspective on current EVM practice. Project Management Journal. 2010. Vol. 41. No. 5, pp. 90-90.

SCHWABLE, K. Řízení projektů v IT, Kompletní průvodce, Brno, Computer Press, 2011. 549 pp.

SIU, MF; LU, M. Scheduling Simulation-Based Techniques for Earned Value Management on Resource-Constrained Schedules Under Delayed Scenarios. In Proceedings of the 2011 Winter Simulation Conference (WSC). New York, USA, 2011, pp. 3455-3466.

Společnost pro projektové řízení Česká republika. [Online], 2014 [cit. 2014-08-04],Available from: http://www.cspr.cz

ŠVIRÁKOVÁ, E. a kol. Chaos a řád v projektovém managementu a marketingových komunikacích. (LACKO, B. Určení stavu projektu jako východisko k jeho racionálnímuřízení v prostředí chaosu. pp. 29-44). Zlín, VeRBuM, 2013. 127 pp.

ZADEH, L., A. Fuzzy sets. Information and Control, 1965. Vol. 8. No. 3, pp. 338-353.

ZIMMERMANN, H. J. Fuzzy Set Theory – and Its Applications . London. Kluwer Academic Publishers. 2001.

Published

2016-11-04

How to Cite

Doskočil, R. (2016). Fuzzy Logic: An Instrument for the Evaluation of Project Status. Journal of Quantitative Methods for Economics and Business Administration, 19, Páginas 5 a 23. https://doi.org/10.46661/revmetodoscuanteconempresa.2213

Issue

Section

Articles