Document Type : Research Paper
Authors
Abstract
Delay is a common occurrence in the country's construction projects. Identifying delay factors in these projects and determining the influence of these factors is necessary to achieve the objectives of management. In this study, the effective delay factors on construction projects are identified by using previous studies, project documents and experts opinions. Since these factors affect on each other, the fuzzy cognitive map has drawn for effective factors and assessment factors or management objectives. Then, the effect of each factor on the assessment factors are evaluated by using hybrid learning algorithm and prioritization factors are done by using fuzzy data envelopment analysis. The results of the survey in West Azerbaijan province show that “supervision technical weaknesses for overcoming technical and executive workshop problems”, “inaccurate estimate of workload, required equipments and project time” and “the multiplicity of decision centers on the doing of projects” are the most important delay factors in construction projects
Keywords
عطافر، علی.، اقبالی، محمد.) 7260 (. آسیب شناسی عوامل مؤثر بر تأخیر در پروژه های منطقة 2
- . عملیات انتقال گاز ایران. مجله مدیریت صنعتی دانشگاه تهران، سال پنجم، شماره دوم، 720 84
Abdul-Rahman, H., Takim, R., & Min, W. S. (2009). Financial-related causes contributing to project delays. Journal of Retail & Leisure Property, 8(3), 225-238.
Al-Hazim, N. (2015). Delay and cost overrun in road construction projects in Jordan. International Journal of Engineering & Technology, 4(2), 288-293.
Assaf, S. A., & Al-Hejji, S. (2006). Causes of delay in large construction projects. International journal of project management, 24(4), 349-357.
Azadeh, A., Ziaei, B., & Moghaddam, M. (2012). A hybrid fuzzy regression-fuzzy cognitive map algorithm for forecasting and optimization of housing market fluctuations. Expert Systems with Applications, 39(1), 298-315.
Baghery, M., Yousefi, S., & Rezaee, M. J. (2016). Risk measurement and prioritization of auto parts manufacturing processes based on process failure analysis, interval data envelopment analysis and grey relational analysis. Journal of Intelligent Manufacturing, DOI: 10.1007/s10845-016-1214-1.
Chen, C. B., & Klein, C. M. (1997). A simple approach to ranking a group of aggregated fuzzy utilities. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 27(1), 26-35.
Chen, Y. C., Chiu, Y. H., Huang, C. W., & Tu, C. H. (2013). The analysis of bank business performance and market risk—Applying Fuzzy DEA. Economic Modelling, 32, 225-232.
Doloi, H., Sawhney, A., Iyer, K. C., & Rentala, S. (2012). Analysing factors affecting delays in Indian construction projects. International Journal of Project Management, 30(4), 479-489.
Doraisamy, S. V., Akasah, Z. A., & Yunus, R. (2015). An Overview on the Issue of Delay in the Construction Industry. In InCIEC 2014, Springer Singapore, 313-319.
Fallahnejad, M. H. (2013). Delay causes in Iran gas pipeline projects. International Journal of Project Management, 31(1), 136-146.
Hu, X., & Liu, C. (2015). Managing undesirable outputs in the Australian construction industry using Data Envelopment Analysis models. Journal of Cleaner Production, 101, 148-157.
Hwang, S. N., Chen, C., Chen, Y., Lee, H. S., & Shen, P. D. (2013). Sustainable design performance evaluation with applications in the automobile industry: Focusing on inefficiency by undesirable factors. Omega, 41(3), 553-558.
Kaliba, C., Muya, M., & Mumba, K. (2009). Cost escalation and schedule delays in road construction projects in Zambia. International Journal of Project Management, 27(5), 522-531.
Kim, S. Y., & Tuan, K. N. (2016). Delay factor analysis for hospital projects in Vietnam. KSCE Journal of Civil Engineering, 20(2), 519-529.
Kosko, B. (1986). Fuzzy cognitive maps. International Journal of man-machine studies, 24(1), 65-75.
Kyriakarakos, G., Patlitzianas, K., Damasiotis, M., & Papastefanakis, D. (2014). A fuzzy cognitive maps decision support system for renewables local planning. Renewable and Sustainable Energy Reviews, 39, 209-222.
Lee, K. C., Lee, H., Lee, N., & Lim, J. (2013). An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms. Industrial Marketing Management, 42(4), 552-563.
Lovell, C. K., & Pastor, J. T. (1999). Radial DEA models without inputs or without outputs. European Journal of Operational Research, 118(1), 46-51.
Papageorgiou, E. I., & Kannappan, A. (2012). Fuzzy cognitive map ensemble learning paradigm to solve classification problems: Application to autism identification. Applied Soft Computing, 12(12), 3798-3809.
Papageorgiou, E. I., Stylios, C., & Groumpos, P. P. (2006). Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links. International Journal of Human-Computer Studies, 64(8), 727-743.
Rezaee, M. J., Izadbakhsh, H., & Yousefi, S. (2016). An improvement approach based on DEA-game theory for comparison of operational and spatial efficiencies in urban transportation systems. KSCE Journal of Civil Engineering, 20(4), 1526-1531.
Rezaee, M. J., Yousefi, S., & Hayati, J. (2016). A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level. Neural Computing and Applications, DOI: 10.1007/s00521-016-2478-2.
Sacchelli, S., & Fabbrizzi, S. (2015). Minimisation of uncertainty in decision-making processes using optimised probabilistic Fuzzy Cognitive Maps: A case study for a rural sector. Socio-Economic Planning Sciences, 52, 31-40.
Sambasivan, M., & Soon, Y. W. (2007). Causes and effects of delays in Malaysian construction industry. International Journal of project management, 25(5), 517-526.
Shafiee, M., Lotfi, F. H., & Saleh, H. (2014). Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach. Applied Mathematical Modelling, 38(21), 5092-5112.
Shivambu, X., & Thwala, W. D. (2014). The causes of delays in the delivery of construction projects: a review of literature. In Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate, Springer Berlin Heidelberg, 715-720.
Storn, R., & Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4), 341-359.
Sweis, G., Sweis, R., Hammad, A. A., & Shboul, A. (2008). Delays in construction projects: The case of Jordan. International Journal of Project Management, 26(6), 665-674.
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
Wanke, P., Barros, C. P., & Emrouznejad, A. (2016). Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks. European Journal of Operational Research, 249(1), 378-389.
Yang, J. B., & Wei, P. R. (2010). Causes of delay in the planning and design phases for construction projects. Journal of Architectural Engineering, 16(2), 80-83.
Zimmermann, H. J. (1975). Description and optimization of fuzzy system. International Journal of General System, 2(1), 209-215.
- . عملیات انتقال گاز ایران. مجله مدیریت صنعتی دانشگاه تهران، سال پنجم، شماره دوم، 720 84
Abdul-Rahman, H., Takim, R., & Min, W. S. (2009). Financial-related causes contributing to project delays. Journal of Retail & Leisure Property, 8(3), 225-238.
Al-Hazim, N. (2015). Delay and cost overrun in road construction projects in Jordan. International Journal of Engineering & Technology, 4(2), 288-293.
Assaf, S. A., & Al-Hejji, S. (2006). Causes of delay in large construction projects. International journal of project management, 24(4), 349-357.
Azadeh, A., Ziaei, B., & Moghaddam, M. (2012). A hybrid fuzzy regression-fuzzy cognitive map algorithm for forecasting and optimization of housing market fluctuations. Expert Systems with Applications, 39(1), 298-315.
Baghery, M., Yousefi, S., & Rezaee, M. J. (2016). Risk measurement and prioritization of auto parts manufacturing processes based on process failure analysis, interval data envelopment analysis and grey relational analysis. Journal of Intelligent Manufacturing, DOI: 10.1007/s10845-016-1214-1.
Chen, C. B., & Klein, C. M. (1997). A simple approach to ranking a group of aggregated fuzzy utilities. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 27(1), 26-35.
Chen, Y. C., Chiu, Y. H., Huang, C. W., & Tu, C. H. (2013). The analysis of bank business performance and market risk—Applying Fuzzy DEA. Economic Modelling, 32, 225-232.
Doloi, H., Sawhney, A., Iyer, K. C., & Rentala, S. (2012). Analysing factors affecting delays in Indian construction projects. International Journal of Project Management, 30(4), 479-489.
Doraisamy, S. V., Akasah, Z. A., & Yunus, R. (2015). An Overview on the Issue of Delay in the Construction Industry. In InCIEC 2014, Springer Singapore, 313-319.
Fallahnejad, M. H. (2013). Delay causes in Iran gas pipeline projects. International Journal of Project Management, 31(1), 136-146.
Hu, X., & Liu, C. (2015). Managing undesirable outputs in the Australian construction industry using Data Envelopment Analysis models. Journal of Cleaner Production, 101, 148-157.
Hwang, S. N., Chen, C., Chen, Y., Lee, H. S., & Shen, P. D. (2013). Sustainable design performance evaluation with applications in the automobile industry: Focusing on inefficiency by undesirable factors. Omega, 41(3), 553-558.
Kaliba, C., Muya, M., & Mumba, K. (2009). Cost escalation and schedule delays in road construction projects in Zambia. International Journal of Project Management, 27(5), 522-531.
Kim, S. Y., & Tuan, K. N. (2016). Delay factor analysis for hospital projects in Vietnam. KSCE Journal of Civil Engineering, 20(2), 519-529.
Kosko, B. (1986). Fuzzy cognitive maps. International Journal of man-machine studies, 24(1), 65-75.
Kyriakarakos, G., Patlitzianas, K., Damasiotis, M., & Papastefanakis, D. (2014). A fuzzy cognitive maps decision support system for renewables local planning. Renewable and Sustainable Energy Reviews, 39, 209-222.
Lee, K. C., Lee, H., Lee, N., & Lim, J. (2013). An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms. Industrial Marketing Management, 42(4), 552-563.
Lovell, C. K., & Pastor, J. T. (1999). Radial DEA models without inputs or without outputs. European Journal of Operational Research, 118(1), 46-51.
Papageorgiou, E. I., & Kannappan, A. (2012). Fuzzy cognitive map ensemble learning paradigm to solve classification problems: Application to autism identification. Applied Soft Computing, 12(12), 3798-3809.
Papageorgiou, E. I., Stylios, C., & Groumpos, P. P. (2006). Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links. International Journal of Human-Computer Studies, 64(8), 727-743.
Rezaee, M. J., Izadbakhsh, H., & Yousefi, S. (2016). An improvement approach based on DEA-game theory for comparison of operational and spatial efficiencies in urban transportation systems. KSCE Journal of Civil Engineering, 20(4), 1526-1531.
Rezaee, M. J., Yousefi, S., & Hayati, J. (2016). A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level. Neural Computing and Applications, DOI: 10.1007/s00521-016-2478-2.
Sacchelli, S., & Fabbrizzi, S. (2015). Minimisation of uncertainty in decision-making processes using optimised probabilistic Fuzzy Cognitive Maps: A case study for a rural sector. Socio-Economic Planning Sciences, 52, 31-40.
Sambasivan, M., & Soon, Y. W. (2007). Causes and effects of delays in Malaysian construction industry. International Journal of project management, 25(5), 517-526.
Shafiee, M., Lotfi, F. H., & Saleh, H. (2014). Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach. Applied Mathematical Modelling, 38(21), 5092-5112.
Shivambu, X., & Thwala, W. D. (2014). The causes of delays in the delivery of construction projects: a review of literature. In Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate, Springer Berlin Heidelberg, 715-720.
Storn, R., & Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4), 341-359.
Sweis, G., Sweis, R., Hammad, A. A., & Shboul, A. (2008). Delays in construction projects: The case of Jordan. International Journal of Project Management, 26(6), 665-674.
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
Wanke, P., Barros, C. P., & Emrouznejad, A. (2016). Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks. European Journal of Operational Research, 249(1), 378-389.
Yang, J. B., & Wei, P. R. (2010). Causes of delay in the planning and design phases for construction projects. Journal of Architectural Engineering, 16(2), 80-83.
Zimmermann, H. J. (1975). Description and optimization of fuzzy system. International Journal of General System, 2(1), 209-215.
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