Monte Carlo Mathematical Model Simulation: An Evaluation of The Probability of Construction Project Acceleration
DOI:
https://doi.org/10.47352/jmans.2774-3047.269Keywords:
Monte Carlo simulation, the Djuanda flyover construction, probability, project accelerationAbstract
Complex projects such as road infrastructure require reliability and risk analysis for safety and economic sustainability. This study divides the concept of comprehensive risk identification into several variables with several indicators. Indicators refer to findings that occur in the field during acceleration. The simulation was conducted with the help of the @Risk program in Microsoft Excel using standard settings, and the distribution used was triangular. The population in this study is all project stakeholders related to determining the implementation time of the Djuanda FO construction, which is currently underway in the 46th week. The population consisted of 22 experts who were involved in scheduling the FO Djuanda construction project. Since the population size is limited in the study, all population members were sampled. The sampling technique is census or saturated sampling, in which all population members are used as samples. The respondents asked to complete a questionnaire and answer questions about implementing the FO Djuanda development project. Sampling is limited to top management with expertise in decision-making to determine the duration of project implementation in scheduling. This study obtained interval data, with interval data in the form of a Likert scale (scale 1–5). Based on the research results, risk evaluation can be adopted well through Monte Carlo mathematical model simulation. The risks in the acceleration of the FO Djuanda development project, based on the order of risk levels from the largest to the smallest, are direct costs, work calendar schedule, logistics, external, field constraints, health and safety, indirect costs, community relations, environment, construction contracts, traffic, and construction.
References
[1] R. Wijaya, J. M. Kerta, and R. Hedwig. (2013). "Influences of wireless traffic toward wifiperformance at BINUS square - Jakarta". Internetworking Indonesia Journal. 5 : 37-41.
[2] M. Ehrlich and R. L. K. Tiong. (2012). "Improving the Assessment of Economic Foreign Exchange Exposure in Public–Private Partnership Infrastructure Projects". Journal of Infrastructure Systems. 18 (2): 57-67. 10.1061/(asce)is.1943-555x.0000069.
DOI: https://doi.org/10.1061/(ASCE)IS.1943-555X.0000069[3] L. D. Nguyen, D. H. Phan, and L. C. M. Tang. (2013). "Simulating Construction Duration for Multistory Buildings with Controlling Activities". Journal of Construction Engineering and Management. 139 (8): 951-959. 10.1061/(asce)co.1943-7862.0000677.
DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000677[4] J. D. Vlok and J. C. Olivier. (2012). "Analytic approximation to the largest eigenvalue distribution of a white Wishart matrix". IET Communications. 6 (12): 1804-1811. 10.1049/iet-com.2011.0843.
DOI: https://doi.org/10.1049/iet-com.2011.0843[5] L. Yu, Y. P. Li, and G. H. Huang. (2016). "A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China". Energy. 98 : 190-203. 10.1016/j.energy.2016.01.021.
DOI: https://doi.org/10.1016/j.energy.2016.01.021[6] F. Al-Sahar. (2019). "Practical Analysis and Response for Risks Using Monte Carlo Simulation on Construction Manufacturing". IOP Conference Series: Materials Science and Engineering. 661 (1). 10.1088/1757-899x/661/1/012132.
DOI: https://doi.org/10.1088/1757-899X/661/1/012132[7] C. A. Peleskei, V. Dorca, R. A. Munteanu, and R. Munteanu. (2015). "Risk Consideration and Cost Estimation in Construction Projects Using Monte Carlo Simulation". Management. 10 : 163-176.
[8] F. Santos, S. F. Garcia, and C. Acosta. (2022). "Comparison of the Different Project Management Software used for a Commercial Project in the Philippines: A Case Study". 2nd International Conference in Information and Computing Research (iCORE). 177-183. 10.1109/iCORE58172.2022.00051.
DOI: https://doi.org/10.1109/iCORE58172.2022.00051[9] L. M. F. Silva, A. C. R. de Oliveira, M. S. A. Leite, and F. A. S. Marins. (2020). "Risk assessment model using conditional probability and simulation: case study in a piped gas supply chain in Brazil". International Journal of Production Research. 59 (10): 2960-2976. 10.1080/00207543.2020.1744764.
DOI: https://doi.org/10.1080/00207543.2020.1744764[10] K. Walȩdzik and J. Mańdziuk. (2018). "Applying hybrid Monte Carlo Tree Search methods to Risk-Aware Project Scheduling Problem". Information Sciences. 460-461 : 450-468. 10.1016/j.ins.2017.08.049.
DOI: https://doi.org/10.1016/j.ins.2017.08.049[11] X. Chen, L. Cheng, G. Deng, S. Guan, and L. Hu. (2021). "Project duration-cost-quality prediction model based on Monte Carlo simulation". Journal of Physics: Conference Series. 1978 (1). 10.1088/1742-6596/1978/1/012048.
DOI: https://doi.org/10.1088/1742-6596/1978/1/012048[12] F. Alves Cantini Cardozo, D. Peixoto Cordova, and C. Otávio Petter. (2022). "Risk analysis by Monte Carlo simulation in underground rock excavation projects". Dyna. 89 (221): 24-30. 10.15446/dyna.v89n221.97628.
DOI: https://doi.org/10.15446/dyna.v89n221.97628[13] F. Amirah, A. Shukri, and Z. Isa. (2023). "Monte Carlo Simulation Based Approach to Quantify Risks for Construction Project Uncertainty Analysis using Probabilistic Estimates in Risk Assessment". Journal of Pharmaceutical Negative Results. 13 : 366-376.
[14] M. Setiawan, W. D. Ruspitasari, and I. K. Ningrum. (2020). "The role of mediation on product innovation and market orientation related to both entrepreneurial orientation and competitive advantage". International Journal of Innovation, Creativity and Change. 13 : 622-639.
[15] H. Yasin, M. Usman, H. Rashid, A. Nasir, A. Sarwar, and I. A. Randhawa. (2017). "Guidelines for Environmental Impact Assessment of JHAL flyover and underpass project in Faisalabad". Geology, Ecology, and Landscapes. 1 (3): 205-212. 10.1080/24749508.2017.1363972.
DOI: https://doi.org/10.1080/24749508.2017.1363972[16] R. M. Choudhry, M. A. Aslam, J. W. Hinze, and F. M. Arain. (2014). "Cost and Schedule Risk Analysis of Bridge Construction in Pakistan: Establishing Risk Guidelines". Journal of Construction Engineering and Management. 140 (7). 10.1061/(asce)co.1943-7862.0000857.
DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000857[17] E. Yuniarti, L. A. S. M. Exposto, I. Dewata, F. A. D. Nugraha, and A. Alfitri. (2024). "Health and Environmental Pollution: A Literature Review". Kesmas National Public Health Journal. 19 (5). 10.21109/kesmas.v19isp1.1102.
DOI: https://doi.org/10.21109/kesmas.v19isp1.1102[18] J. Eliáš, M. Vořechovský, and V. Sadílek. (2020). "Periodic version of the minimax distance criterion for Monte Carlo integration". Advances in Engineering Software. 149. 10.1016/j.advengsoft.2020.102900.
DOI: https://doi.org/10.1016/j.advengsoft.2020.102900[19] D. Pant and K. Srinivas. (2019). "Cost Estimation of Construction Project Using Monte Carlo Simulation". IOSR Journal of Mechanical and Civil Engineering. 16 : 13-19
[20] W. E. Back and L. C. Bell. (1995). "Monte Carlo Simulation as Tool for Process Reengineering". Journal of Management in Engineering. 11 (5): 46-53. 10.1061/(asce)0742-597x(1995)11:5(46).
DOI: https://doi.org/10.1061/(ASCE)0742-597X(1995)11:5(46)[21] Y. Chen, S. Chen, C. Hu, L. Jin, and X. Zheng. (2020). "Novel Probabilistic Cost Estimation Model Integrating Risk Allocation and Claim in Hydropower Project". Journal of Construction Engineering and Management. 146 (8). 10.1061/(asce)co.1943-7862.0001893.
DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001893[22] J. Du, B.-C. Kim, and D. Zhao. (2016). "Cost Performance as a Stochastic Process: EAC Projection by Markov Chain Simulation". Journal of Construction Engineering and Management. 142 (6). 10.1061/(asce)co.1943-7862.0001115.
DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001115[23] Z. Bouayed. (2016). "Using monte carlo simulation to mitigate the risk of project cost overruns". International Journal of Safety and Security Engineering. 6 (2): 293-300. 10.2495/safe-v6-n2-293-300.
DOI: https://doi.org/10.2495/SAFE-V6-N2-293-300[24] E. Eshtehardian and S. Khodaverdi. (2016). "A Multiply Connected Belief Network approach for schedule risk analysis of metropolitan construction projects". Civil Engineering and Environmental Systems. 33 (3): 227-246. 10.1080/10286608.2016.1184492.
DOI: https://doi.org/10.1080/10286608.2016.1184492[25] J. Batselier and M. Vanhoucke. (2015). "Empirical Evaluation of Earned Value Management Forecasting Accuracy for Time and Cost". Journal of Construction Engineering and Management. 141 (11). 10.1061/(asce)co.1943-7862.0001008.
DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001008[26] M.-H. Kim and E.-B. Lee. (2019). "A Forecast Model for the Level of Engineering Maturity Impact on Contractor’s Procurement and Construction Costs for Offshore EPC Megaprojects". Energies. 12 (12). 10.3390/en12122295.
DOI: https://doi.org/10.3390/en12122295[27] X. Zhu. (2018). "Rural Infrastructure PPP Project Risks Analysis Based on Monte Carlo Method". Proceedings of the 2018 3rd International Conference on Education, E-learning and Management Technology (EEMT 2018). 10.2991/iceemt-18.2018.26.
DOI: https://doi.org/10.2991/iceemt-18.2018.26[28] W. Fawcett, I. R. Urquijo, H. Krieg, M. Hughes, L. Mikalsen, and Ó. R. R. Gutiérrez. (2015). "Cost and Environmental Evaluation of Flexible Strategies for a Highway Construction Project under Traffic Growth Uncertainty". Journal of Infrastructure Systems. 21 (3). 10.1061/(asce)is.1943-555x.0000230.
DOI: https://doi.org/10.1061/(ASCE)IS.1943-555X.0000230[29] S.-n. Sun and Z.-b. Su. (2011). "Parametric vibration of submerged floating tunnel tether under random excitation". China Ocean Engineering. 25 (2): 349-356. 10.1007/s13344-011-0029-2.
DOI: https://doi.org/10.1007/s13344-011-0029-2[30] A. Senova, A. Tobisova, and R. Rozenberg. (2023). "New Approaches to Project Risk Assessment Utilizing the Monte Carlo Method". Sustainability. 15 (2). 10.3390/su15021006.
DOI: https://doi.org/10.3390/su15021006[31] F. Allahi, L. Cassettari, and M. Mosca. (2017). "Stochastic risk analysis and cost contingency allocation approach for construction projects applying Monte Carlo simulation". Lecture Notes in Engineering and Computer Science. 2229 : 385-391.
[32] M. K. Sharma. (2020). "Monte Carlo Simulation Applications for Construction Project Management". International Journal of Civil Engineering and Technology (Ijciet). 11 (2). 10.34218/ijciet.11.2.2020.010.
DOI: https://doi.org/10.34218/IJCIET.11.2.2020.010
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