A Step-By-Step Hybrid Approach Based on Multi-Criteria Decision-Making Methods And A Bi-Objective Optimization Model To Project Risk Management

Mohammad Khalilzadeh; Sayyid Ali Banihashemi; Darko Božanić

doi:10.31181/dmame712024884

Authors

Mohammad Khalilzadeh CENTRUM Católica Graduate Business School, Lima, Peru. Pontificia Universidad Católica del Perú, Lima, Peru https://orcid.org/0000-0002-2373-8505
Sayyid Ali Banihashemi Department of Industrial Engineering, Payame Noor University, Tehran, Iran https://orcid.org/0000-0003-4676-2847
Darko Božanić Military academy, University of Defence in Belgrade, Belgrade, Serbia https://orcid.org/0000-0002-9657-0889

DOI:

https://doi.org/10.31181/dmame712024884

Keywords:

Project risk management, Fuzzy BWM, Fuzzy WASPAS, bi-objective mathematical model, Augmented Epsilon-Constraint

Abstract

Project success and achieving project objectives and goals highly depend on effective and thorough risk management implementation. This study provides a comprehensive and practical methodology for project risk management. In this paper, firstly, the risks were collected by analyzing the historical documents and literature. Then, the collected risks were screened using brainstorming and categorized into five groups. Subsequently, a questionnaire was made and the identified risks were validated using the Fuzzy Delphi technique. Also, the relationships between risks were determined using the Interpretive Structural Modelling (ISM) method. Moreover, the weights of the criteria used to rank the risks were calculated through the Fuzzy Best-Worst Method. Subsequently, the major risks were determined using the fuzzy WASPAS method. Furthermore, a novel bi-objective mathematical programming model was developed and solved using the Augmented Epsilon-Constraint (AEC) method to choose the optimal risk response strategies for each critical risk. The results demonstrated that the proposed framework is effective in dealing with construction project risks.

Downloads

Download data is not yet available.

References

Burr, A., Barber, F., Briggs, S., Breyer, W., Castellano, J., Gibbs, D. J., ... & Pickavance, K. (2016). Delay and disruption in construction contracts. Informa Law from Routledge. https://doi.org/10.4324/9781315673950

Arditi, D., Nayak, S., & Damci, A. (2017). Effect of organizational culture on delay in construction. International journal of project management, 35(2), 136-147. https://doi.org/10.1016/j.ijproman.2016.10.018

Muriana, C., & Vizzini, G. (2017). Project risk management: A deterministic quantitative technique for assessment and mitigation. International Journal of Project Management, 35(3), 320-340. https://doi.org/10.1016/j.ijproman.2017.01.010

Zhang, Y., & Fan, Z. P. (2014). An optimization method for selecting project risk response strategies. International journal of project management, 32(3), 412-422. https://doi.org/10.1016/j.ijproman.2013.06.006

Wu, D., Li, J., Xia, T., Bao, C., Zhao, Y., & Dai, Q. (2018). A multiobjective optimization method considering process risk correlation for project risk response planning. Information Sciences, 467, 282-295. https://doi.org/10.1016/j.ins.2018.07.013

Zou, P. X., Zhang, G., & Wang, J. (2007). Understanding the key risks in construction projects in China. International journal of project management, 25(6), 601-614. https://doi.org/10.1016/j.ijproman.2007.03.001

Dziadosz, A., & Rejment, M. (2015). Risk analysis in construction project-chosen methods. Procedia Engineering, 122, 258-265. https://doi.org/10.1016/j.proeng.2015.10.034

Murray-Webster, R., & Hillson, D. (2021). Making risky and important decisions: A leader’s guide. CRC Press. https://doi.org/10.1201/9781003145134

Carvalho, M. M. D., & Rabechini Junior, R. (2015). Impact of risk management on project performance: the importance of soft skills. International journal of production research, 53(2), 321-340. https://doi.org/10.1080/00207543.2014.919423

Ahmadi, M., Behzadian, K., Ardeshir, A., & Kapelan, Z. (2017). Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects. Journal of Civil Engineering and Management, 23(2), 300-310. https://doi.org/10.3846/13923730.2015.1068847

Fernando, C. K., Hosseini, M. R., Zavadskas, E. K., Perera, B. A. K. S., & Rameezdeen, R. (2017). Managing the financial risks affecting construction contractors: implementing hedging in Sri Lanka. International Journal of Strategic Property Management, 21(2), 212-224. https://doi.org/10.3846/1648715X.2017.1301592

Dehdasht, G., Mohamad Zin, R., Ferwati, M. S., Mohammed Abdullahi, M. A., Keyvanfar, A., & McCaffer, R. (2017). DEMATEL-ANP risk assessment in oil and gas construction projects. Sustainability, 9(8), 1420. https://doi.org/10.3390/su9081420

Fattahi, R., & Khalilzadeh, M. (2018). Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Safety science, 102, 290-300. https://doi.org/10.1016/j.ssci.2017.10.018

Rahimi, Y., Tavakkoli-Moghaddam, R., Iranmanesh, S. H., & Vaez-Alaei, M. (2018). Hybrid approach to construction project risk management with simultaneous FMEA/ISO 31000/evolutionary algorithms: Empirical optimization study. Journal of construction engineering and management, 144(6), 04018043. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001486

Kassem, M. A., Khoiry, M. A., & Hamzah, N. (2019). Risk factors in oil and gas construction projects in developing countries: A case study. International Journal of Energy Sector Management, 13(4), 846-861. https://doi.org/10.1108/IJESM-11-2018-0002

Mahmoudi, A., Abbasi, M., Deng, X., Ikram, M., & Yeganeh, S. (2020). A novel model for risk management of outsourced construction projects using decision-making methods: a case study. Grey Systems: Theory and Application, 10(2), 97-123. https://doi.org/10.1108/GS-09-2019-0038

Zhang, H., & Sun, Q. (2019). An integrated MCDM approach to train derailment risk response strategy selection. Symmetry, 12(1), 47. https://doi.org/10.3390/sym12010047

Badalpur, M., & Nurbakhsh, E. (2021). An application of WASPAS method in risk qualitative analysis: a case study of a road construction project in Iran. International Journal of Construction Management, 21(9), 910-918. https://doi.org/10.1080/15623599.2019.1595354

Khalilzadeh, M., Ghasemi, P., Afrasiabi, A., & Shakeri, H. (2021). Hybrid fuzzy MCDM and FMEA integrating with linear programming approach for the health and safety executive risks: a case study. Journal of modelling in management, 16(4), 1025-1053. https://doi.org/10.1108/JM2-12-2019-0285

Hiyassat, M. A., Alkasagi, F., El-Mashaleh, M., & Sweis, G. J. (2022). Risk allocation in public construction projects: the case of Jordan. International journal of construction management, 22(8), 1478-1488. https://doi.org/10.1080/15623599.2020.1728605

Erol, H., Dikmen, I., Atasoy, G., & Birgonul, M. T. (2022). An analytic network process model for risk quantification of mega construction projects. Expert Systems with Applications, 191, 116215. https://doi.org/10.1016/j.eswa.2021.116215

Siraj, N. B., & Fayek, A. R. (2019). Risk identification and common risks in construction: Literature review and content analysis. Journal of construction engineering and management, 145(9), 03119004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001685

Zhang, J. (2017). Evaluating regional low-carbon tourism strategies using the fuzzy Delphi-analytic network process approach. Journal of Cleaner Production, 141, 409-419. https://doi.org/10.1016/j.jclepro.2016.09.122

Pathinathan, T., & Ponnivalavan, K. (2015). Reverse order triangular, trapezoidal and pentagonal fuzzy numbers. Annals of Pure and Applied Mathematics, 9(1), 107-117. http://www.researchmathsci.org/apamart/APAM-v9n1-12.pdf

Can, G. F., & Toktas, P. (2018). A novel fuzzy risk matrix based risk assessment approach. Kybernetes, 47(9), 1721-1751. https://doi.org/10.1108/K-12-2017-0497

Wu, H. Y., Tzeng, G. H., & Chen, Y. H. (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert systems with applications, 36(6), 10135-10147. https://doi.org/10.1016/j.eswa.2009.01.005

Afrasiabi, A., Chalmardi, M. K., & Balezentis, T. (2022). A novel hybrid evaluation framework for public organizations based on employees’ performance factors. Evaluation and Program Planning, 91, 102020. https://doi.org/10.1016/j.evalprogplan.2021.102020

Afrasiabi, A., Tavana, M., & Di Caprio, D. (2022). An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection. Environmental Science and Pollution Research, 29(25), 37291-37314. https://doi.org/10.1007/s11356-021-17851-2

Ishikawa, A., Amagasa, M., Shiga, T., Tomizawa, G., Tatsuta, R., & Mieno, H. (1993). The max-min Delphi method and fuzzy Delphi method via fuzzy integration. Fuzzy sets and systems, 55(3), 241-253. https://doi.org/10.1016/0165-0114(93)90251-C

Vermunt, A. H., Smits, M. T., Noorderhaven, N. G., & Hofstede, G. J. (1997). Wired international teams: Experiments in strategic decision making by multi-cultural virtual teams. In Proceedings of the 5th European Conference on Information Systems (ECIS) (pp. 321-336). Loebbecke. https://pure.uvt.nl/ws/portalfiles/portal/204522/annelies74098.pdf

Padilla-Rivera, A., do Carmo, B. B. T., Arcese, G., & Merveille, N. (2021). Social circular economy indicators: Selection through fuzzy delphi method. Sustainable Production and Consumption, 26, 101-110. https://doi.org/10.1016/j.spc.2020.09.015

Warfield, J. N. (1974). Developing interconnection matrices in structural modeling. IEEE Transactions on Systems, Man, and Cybernetics, (1), 81-87. https://doi.org/10.1109/TSMC.1974.5408524

Agarwal, A., Shankar, R., & Tiwari, M. K. (2007). Modeling agility of supply chain. Industrial marketing management, 36(4), 443-457. https://doi.org/10.1016/j.indmarman.2005.12.004

Zayed, E. O., & Yaseen, E. A. (2021). Barriers to sustainable supply chain management implementation in Egyptian industries: an interpretive structural modeling (ISM) approach. Management of environmental quality: an international journal, 32(6), 1192-1209. https://doi.org/10.1108/MEQ-12-2019-0271

Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23-31. https://doi.org/10.1016/j.knosys.2017.01.010

Kannan, D., Moazzeni, S., mostafayi Darmian, S., & Afrasiabi, A. (2021). A hybrid approach based on MCDM methods and Monte Carlo simulation for sustainable evaluation of potential solar sites in east of Iran. Journal of Cleaner Production, 279, 122368. https://doi.org/10.1016/j.jclepro.2020.122368

Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009

Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130. https://doi.org/10.1016/j.omega.2015.12.001

Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika, 122(6), 3-6. https://doi.org/10.5755/j01.eee.122.6.1810

Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2015). Selecting a contractor by using a novel method for multiple attribute analysis: Weighted Aggregated Sum Product Assessment with grey values (WASPAS-G). Studies in Informatics and Control, 24(2), 141-150. https://doi.org/10.24846/v24i2y201502

Elbarkouky, M. M., Fayek, A. R., Siraj, N. B., & Sadeghi, N. (2016). Fuzzy arithmetic risk analysis approach to determine construction project contingency. Journal of construction engineering and management, 142(12), 04016070. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001191

Aziz, R. F. (2013). Ranking of delay factors in construction projects after Egyptian revolution. Alexandria Engineering Journal, 52(3), 387-406. https://doi.org/10.1016/j.aej.2013.03.002

Khodeir, L. M., & Mohamed, A. H. M. (2015). Identifying the latest risk probabilities affecting construction projects in Egypt according to political and economic variables. From January 2011 to January 2013. HBRC journal, 11(1), 129-135. https://doi.org/10.1016/j.hbrcj.2014.03.007

Marzouk, M. M., & El-Rasas, T. I. (2014). Analyzing delay causes in Egyptian construction projects. Journal of advanced research, 5(1), 49-55. https://doi.org/10.1016/j.jare.2012.11.005

Liu, J., Zhao, X., & Yan, P. (2016). Risk paths in international construction projects: Case study from Chinese contractors. Journal of construction engineering and management, 142(6), 05016002. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001116

Adeleke, A. Q., Bahaudin, A. Y., Kamaruddeen, A. M., Bamgbade, J. A., Salimon, M. G., Khan, M. W. A., & Sorooshian, S. (2018). The influence of organizational external factors on construction risk management among Nigerian construction companies. Safety and health at work, 9(1), 115-124. https://doi.org/10.1016/j.shaw.2017.05.004

Koulinas, G. K., Marhavilas, P. K., Demesouka, O. E., Vavatsikos, A. P., & Koulouriotis, D. E. (2019). Risk analysis and assessment in the worksites using the fuzzy-analytical hierarchy process and a quantitative technique–A case study for the Greek construction sector. Safety science, 112, 96-104. https://doi.org/10.1016/j.ssci.2018.10.017

Puška, A., Nedeljković, M., Prodanović, R., Vladisavljević, R., & Suzić, R. (2022). Market Assessment of Pear Varieties in Serbia Using Fuzzy CRADIS and CRITIC Methods. Agriculture, 12(2), 139. https://doi.org/10.3390/agriculture12020139

Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., & Pamučar, D. (2021). Application of Interval Fuzzy Logic in Selecting a Sustainable Supplier on the Example of Agricultural Production. Symmetry, 13(5), 774. https://doi.org/10.3390/sym13050774

Mohan, V., Ota, M., & Iqbal, P. A. (2023). Comparative Study to Find the Optimal Ordering Quantity of the Risk-Neutral and Risk-Averse Newsvendor. Yugoslav Journal Of Operations Research, 33(3), 323-340. http://dx.doi.org/10.2298/YJOR210815015M

Puška, A., Kozarević, S., Stević, Ž., & Stovrag, J. (2018). A new way of applying interval fuzzy logic in group decision making for supplier selection. Economic Computation and Economic Cybernetics Studies and Research, 52(2), 217-234. https://doi.org/10.24818/18423264/52.2.18.13

Karunathilake, H., Bakhtavar, E., Chhipi-Shrestha, G., Mian, H. R., Hewage, K., & Sadiq, R. (2020). Decision making for risk management: a multi-criteria perspective. In Methods in chemical process safety (Vol. 4, pp. 239-287). Elsevier. https://doi.org/10.1016/bs.mcps.2020.02.004