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Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3)

Year 2022, Volume: 33 Issue: 4, 12119 - 12142, 01.07.2022
https://doi.org/10.18400/tekderg.745510

Abstract

The performance of the Public Private Partnership (PPP) projects depends on the efficiency of the risk allocation strategies between the public and private parties. Therefore, a multi agent system-based Risk Allocation Model for PPP projects (RAMP3) was developed to determine the proper risk allocation decisions between the public and private parties within the study. The methodology of RAMP3 involves i) identification of risks by agents, ii) assessment of each risk’s importance and impact, iii) communication of agents to negotiate on risk allocation decision and iv) determination of strategies and utility functions to be used in negotiation process. Focus of the study is presenting the steps of negotiation process of agents using economic theory and Zeuthen bargaining strategy. RAMP3 was validated on two real PPP projects and results show that the higher risk value of an agent gets, agent’s utility due to counter agent in that concession round lowers. Preliminary findings also show that risk is allocated to the party that has a higher risk acceptability in negotiation process. The RAMP3 will enable project parties to determine the appropriate risk allocation strategies by considering the effects of emerging risks in terms of time delay, cost overrun and conflict and provide contract success. The model can also be used as a decision support system by public partner for performing an efficient and accurate risk allocation.

Supporting Institution

Coordinatorship of Scientific Research Projects of Yildiz Technical University

Project Number

2014-05-01-DOP03

References

  • Ke, Y., Wang, S., Chan, A. P., Lam, P. T. I., Preferred Risk Allocation in China’s Public–Private Partnership (PPP) Projects, International Journal of Project Management, 28(5), 482–492, 2010.
  • Hwang, B. G., Zhao, X., Gay, M. J.S., Public Private Partnership Projects in Singapore: Factors, Critical Risks and Preferred Risk Allocation from the Perspective of Contractor, International Journal of Project Management, 31(3), 424-433, 2013.
  • Gross, M. E., Aligning Public-Private Partnership Contracts with Public Objectives for Transportation Infrastructure, Doctoral Thesis, Virginia Polytechnic Institute and State University, 2010.
  • Yun-na, W. U., Xin-liang, H. U., Ling-shuang, X. U., Ze-zhong, L., Research on Risk Allocation of Public-Private Partnership Projects Based on Rough Set Theory, Communications in Information Science and Management Engineering, 2(7), 15-20, 2012.
  • Marques, R. C., Berg, S., Risks, Contracts, and Private-Sector Participation in Infrastructure, Journal of Construction Engineering and Management, 137(11), 925-932, 2011.
  • Thomas, A. V., Kalidindi, S. N., Ananthanarayanan, K., Risk Perception Analysis of BOT Road Project Participants in India, Construction Management and Economics, 21(4), 393–407, 2003.
  • Lam, K. C., Wang, D., Lee, T. K. P., Tsang, Y. T., Modelling Risk Allocation Decision in Construction Contracts, International Journal of Project Management, 25(5), 485–493, 2000.
  • Ren, Z., Anumba, C. J., Multi-Agent Systems in Construction–State of The Art and Prospects, Automation in Construction, 13(3), 421-434, 2004.
  • Zhu, L., Zhao, X., Chua, D. K. H. Agent-Based Debt Terms’ Bargaining Model to Improve Negotiation Inefficiency in PPP Projects. Journal of Computing in Civil Engineering, 30(6), 04016014, 2016.
  • Ke, Y., Wang, S., Chan, A., Cheung, E., Research Trends of PPP in Construction Journal, Journal of Construction Engineering and Management, 135(10), 1076–1086, 2009.
  • Chengshuang, S., Guochang, Risk Management Framework of Multi-agent System for Construction Projects. Journal of Northeast Forestry University, 1-5, 2006.
  • Li, B., Ren, Z., Bayesian Technique Framework for Allocating Demand Risk Between The Public and Private Sector in PPP Projects, 6th International Conference on Service Systems and Service Management, China, 2009.
  • Karakas, K., Dikmen, I., Birgonul, M.T., Multiagent System to Simulate Risk-Allocation and Cost-Sharing Processes in Construction Projects, Journal of Computing in Civil Engineering, 27(3), 307-319, 2013.
  • Taillandier, F., Taillandier, P., Tepeli, E., Breysse, D., Mehdizadeh, R., Khartabil, F., A Multi-Agent Model to Manage Risks in Construction Project (SMACC). Automation in Construction, 58, 1-18, 2015.
  • Karakaş, K., Development of A Multi Agent System for Negotiation of Cost Overrun in International Construction Projects, Master of Science Thesis, Middle East Technical University, 2010.
  • Dikmen, İ., Birgönül, M. T., Tanyer, A. M., Alparslan, F. N., Uluslararası İnşaat Projeleri İçin Çok Aracılı Bir Risk Modelleme Platformunun Geliştirilmesi, TÜBİTAK Project Report, Project No: 107M334, 2010.
  • Dağkıran, G., A Multi Agent Risk Analysis and Sharing Platform for International Construction Projects Doctoral Thesis, Middle East Technical University, 2015.
  • Python, https://www.python.org/ 29 July 2019.
  • Prechelt, L. An empirical Comparison of C, C++, Java, Perl, Python, Rexx And Tcl. IEEE Computer, 33(10), 23-29, 2000.
  • Sycara, K., Dai, T. Agent Reasoning in Negotiation. In: Kilgour D., Eden C. (eds) Handbook of Group Decision and Negotiation. Advances in Group Decision and Negotiation, vol 4. Springer, Dordrecht, 2010.
  • Ren, Z., Anumba, C. J., Ugwu, O. O., Negotiation in a Multi-Agent System for Construction Claims Negotiation, Applied Artificial Intelligence, 16(5), 359-394, 2002.
  • Ren, Z., Anumba, C. J., Ugwu, O. O., The Development of a Multi-Agent System for Construction Claims Negotiation, Advances in Engineering Software, 34(11), 683-696, 2003a.
  • Ren, Z., Anumba, C. J., Ugwu, O. O., Multiagent System for Construction Claims Negotiatio, Journal of Computing in Civil Engineering, 17(3), 80-188, 2003b.
  • Jennings, N. R., Faratin, P., Lomuscio, A. R., Parsons, S., Sierra, C., Wooldridge, M., Automated Negotiation: Prospects, Methods and Challenges, International Journal of Group Decision and Negotiation, 10(2), 199–215, 2001.
  • Fidan, G., Dikmen, I., Birgonul, M. T., Using Multi Agent Systems in Construction Claim Negotiation, International Conference on Computing in Civil and Building Engineering and XVII Workshop on Intelligent Computing in Engineering, Nottingham-UK, 2010.
  • Young, O.R., Bargaining: Formal Theories of Negotiation. University of Illinois Press, Urbana, 1975.
  • Ren, Z., Anumba, C.J., Ugwu, O. O., Construction Claims Management: Towards an Agent‐Based Approach, Engineering Construction and Architectural Management, 8(3), 185-197, 2001.
  • Rosenschein, J. S., Zlotkin, G., Rules of Encounter: Designing Conventions for Automated Negotiation Among Computers, MIT Press, Cambridge, MA, 1994.
  • Aladağ, H.. Multi-Agent Risk Allocation Model for Build-Operate-Transfer (BOT) Type Transportation Projects, Doctoral Dissertation, Yildiz Technical University, 2016.

Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3)

Year 2022, Volume: 33 Issue: 4, 12119 - 12142, 01.07.2022
https://doi.org/10.18400/tekderg.745510

Abstract

The performance of the Public Private Partnership (PPP) projects depends on the efficiency of the risk allocation strategies between the public and private parties. Therefore, a multi agent system-based Risk Allocation Model for PPP projects (RAMP3) was developed to determine the proper risk allocation decisions between the public and private parties within the study. The methodology of RAMP3 involves i) identification of risks by agents, ii) assessment of each risk’s importance and impact, iii) communication of agents to negotiate on risk allocation decision and iv) determination of strategies and utility functions to be used in negotiation process. Focus of the study is presenting the steps of negotiation process of agents using economic theory and Zeuthen bargaining strategy. RAMP3 was validated on two real PPP projects and results show that the higher risk value of an agent gets, agent’s utility due to counter agent in that concession round lowers. Preliminary findings also show that risk is allocated to the party that has a higher risk acceptability in negotiation process. The RAMP3 will enable project parties to determine the appropriate risk allocation strategies by considering the effects of emerging risks in terms of time delay, cost overrun and conflict and provide contract success. The model can also be used as a decision support system by public partner for performing an efficient and accurate risk allocation.

Project Number

2014-05-01-DOP03

References

  • Ke, Y., Wang, S., Chan, A. P., Lam, P. T. I., Preferred Risk Allocation in China’s Public–Private Partnership (PPP) Projects, International Journal of Project Management, 28(5), 482–492, 2010.
  • Hwang, B. G., Zhao, X., Gay, M. J.S., Public Private Partnership Projects in Singapore: Factors, Critical Risks and Preferred Risk Allocation from the Perspective of Contractor, International Journal of Project Management, 31(3), 424-433, 2013.
  • Gross, M. E., Aligning Public-Private Partnership Contracts with Public Objectives for Transportation Infrastructure, Doctoral Thesis, Virginia Polytechnic Institute and State University, 2010.
  • Yun-na, W. U., Xin-liang, H. U., Ling-shuang, X. U., Ze-zhong, L., Research on Risk Allocation of Public-Private Partnership Projects Based on Rough Set Theory, Communications in Information Science and Management Engineering, 2(7), 15-20, 2012.
  • Marques, R. C., Berg, S., Risks, Contracts, and Private-Sector Participation in Infrastructure, Journal of Construction Engineering and Management, 137(11), 925-932, 2011.
  • Thomas, A. V., Kalidindi, S. N., Ananthanarayanan, K., Risk Perception Analysis of BOT Road Project Participants in India, Construction Management and Economics, 21(4), 393–407, 2003.
  • Lam, K. C., Wang, D., Lee, T. K. P., Tsang, Y. T., Modelling Risk Allocation Decision in Construction Contracts, International Journal of Project Management, 25(5), 485–493, 2000.
  • Ren, Z., Anumba, C. J., Multi-Agent Systems in Construction–State of The Art and Prospects, Automation in Construction, 13(3), 421-434, 2004.
  • Zhu, L., Zhao, X., Chua, D. K. H. Agent-Based Debt Terms’ Bargaining Model to Improve Negotiation Inefficiency in PPP Projects. Journal of Computing in Civil Engineering, 30(6), 04016014, 2016.
  • Ke, Y., Wang, S., Chan, A., Cheung, E., Research Trends of PPP in Construction Journal, Journal of Construction Engineering and Management, 135(10), 1076–1086, 2009.
  • Chengshuang, S., Guochang, Risk Management Framework of Multi-agent System for Construction Projects. Journal of Northeast Forestry University, 1-5, 2006.
  • Li, B., Ren, Z., Bayesian Technique Framework for Allocating Demand Risk Between The Public and Private Sector in PPP Projects, 6th International Conference on Service Systems and Service Management, China, 2009.
  • Karakas, K., Dikmen, I., Birgonul, M.T., Multiagent System to Simulate Risk-Allocation and Cost-Sharing Processes in Construction Projects, Journal of Computing in Civil Engineering, 27(3), 307-319, 2013.
  • Taillandier, F., Taillandier, P., Tepeli, E., Breysse, D., Mehdizadeh, R., Khartabil, F., A Multi-Agent Model to Manage Risks in Construction Project (SMACC). Automation in Construction, 58, 1-18, 2015.
  • Karakaş, K., Development of A Multi Agent System for Negotiation of Cost Overrun in International Construction Projects, Master of Science Thesis, Middle East Technical University, 2010.
  • Dikmen, İ., Birgönül, M. T., Tanyer, A. M., Alparslan, F. N., Uluslararası İnşaat Projeleri İçin Çok Aracılı Bir Risk Modelleme Platformunun Geliştirilmesi, TÜBİTAK Project Report, Project No: 107M334, 2010.
  • Dağkıran, G., A Multi Agent Risk Analysis and Sharing Platform for International Construction Projects Doctoral Thesis, Middle East Technical University, 2015.
  • Python, https://www.python.org/ 29 July 2019.
  • Prechelt, L. An empirical Comparison of C, C++, Java, Perl, Python, Rexx And Tcl. IEEE Computer, 33(10), 23-29, 2000.
  • Sycara, K., Dai, T. Agent Reasoning in Negotiation. In: Kilgour D., Eden C. (eds) Handbook of Group Decision and Negotiation. Advances in Group Decision and Negotiation, vol 4. Springer, Dordrecht, 2010.
  • Ren, Z., Anumba, C. J., Ugwu, O. O., Negotiation in a Multi-Agent System for Construction Claims Negotiation, Applied Artificial Intelligence, 16(5), 359-394, 2002.
  • Ren, Z., Anumba, C. J., Ugwu, O. O., The Development of a Multi-Agent System for Construction Claims Negotiation, Advances in Engineering Software, 34(11), 683-696, 2003a.
  • Ren, Z., Anumba, C. J., Ugwu, O. O., Multiagent System for Construction Claims Negotiatio, Journal of Computing in Civil Engineering, 17(3), 80-188, 2003b.
  • Jennings, N. R., Faratin, P., Lomuscio, A. R., Parsons, S., Sierra, C., Wooldridge, M., Automated Negotiation: Prospects, Methods and Challenges, International Journal of Group Decision and Negotiation, 10(2), 199–215, 2001.
  • Fidan, G., Dikmen, I., Birgonul, M. T., Using Multi Agent Systems in Construction Claim Negotiation, International Conference on Computing in Civil and Building Engineering and XVII Workshop on Intelligent Computing in Engineering, Nottingham-UK, 2010.
  • Young, O.R., Bargaining: Formal Theories of Negotiation. University of Illinois Press, Urbana, 1975.
  • Ren, Z., Anumba, C.J., Ugwu, O. O., Construction Claims Management: Towards an Agent‐Based Approach, Engineering Construction and Architectural Management, 8(3), 185-197, 2001.
  • Rosenschein, J. S., Zlotkin, G., Rules of Encounter: Designing Conventions for Automated Negotiation Among Computers, MIT Press, Cambridge, MA, 1994.
  • Aladağ, H.. Multi-Agent Risk Allocation Model for Build-Operate-Transfer (BOT) Type Transportation Projects, Doctoral Dissertation, Yildiz Technical University, 2016.
There are 29 citations in total.

Details

Primary Language English
Subjects Civil Engineering
Journal Section Articles
Authors

Hande Aladağ 0000-0001-7627-8699

Zeynep Işık 0000-0001-8825-0001

Project Number 2014-05-01-DOP03
Publication Date July 1, 2022
Submission Date May 30, 2020
Published in Issue Year 2022 Volume: 33 Issue: 4

Cite

APA Aladağ, H., & Işık, Z. (2022). Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3). Teknik Dergi, 33(4), 12119-12142. https://doi.org/10.18400/tekderg.745510
AMA Aladağ H, Işık Z. Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3). Teknik Dergi. July 2022;33(4):12119-12142. doi:10.18400/tekderg.745510
Chicago Aladağ, Hande, and Zeynep Işık. “Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3)”. Teknik Dergi 33, no. 4 (July 2022): 12119-42. https://doi.org/10.18400/tekderg.745510.
EndNote Aladağ H, Işık Z (July 1, 2022) Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3). Teknik Dergi 33 4 12119–12142.
IEEE H. Aladağ and Z. Işık, “Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3)”, Teknik Dergi, vol. 33, no. 4, pp. 12119–12142, 2022, doi: 10.18400/tekderg.745510.
ISNAD Aladağ, Hande - Işık, Zeynep. “Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3)”. Teknik Dergi 33/4 (July 2022), 12119-12142. https://doi.org/10.18400/tekderg.745510.
JAMA Aladağ H, Işık Z. Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3). Teknik Dergi. 2022;33:12119–12142.
MLA Aladağ, Hande and Zeynep Işık. “Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3)”. Teknik Dergi, vol. 33, no. 4, 2022, pp. 12119-42, doi:10.18400/tekderg.745510.
Vancouver Aladağ H, Işık Z. Multi Agent System Based Risk Allocation Model for Public-Private-Partnership Type Projects (RAMP3). Teknik Dergi. 2022;33(4):12119-42.