Integration of discrete event simulation with other modeling techniques to simulate construction engineering and management: an overview

Authors

  • Felipe Araya Departamento de Obras Civiles, Universidad Técnica Federico Santa Maria, Valparaíso (Chile)

DOI:

https://doi.org/10.7764/RDLC.21.2.338

Keywords:

review article, discrete event simulation, construction engineering and management

Abstract

Although Discrete Event Simulation (DES) has been the preferred simulation technique in construction operation studies, it suffers from limitations, such as narrowed focus at the operational level. To minimize the effect of DES limitations, researchers have proposed the integration of DES with other simulation techniques, such as agent-based modeling (ABM), system dynamics (SD), and virtual environments (VE). However, limited studies have discussed whether this integration process minimizes DES’ limitations and to what extent. This study summarizes 99 journal manuscripts in the existing literature published between 2010-2020, focusing on integrating DES with ABM, SD, and VE. This study found that the integration of DES with ABM, SD, and VE addressed multiple of DES’ limitations, namely, the lack of human behaviors in process-oriented modeling, the limited strategic perspective, and challenges related to the verification and validation of DES models’ outputs. Ultimately, this study calls for future studies to evaluate the simultaneous integration of DES, ABM, and SD modeling techniques so the complexity of construction projects can be truly accounted for, as comprehensive simulation tools will require the integration of multiple methods to counterbalance their limitations.

 

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References

Abbasi, S., Taghizade, K., & Noorzai, E. (2020). BIM-Based Combination of Takt Time and Discrete Event Simulation for Implementing Just in Time in Construction Scheduling under Constraints. Journal of Construction Engineering and Management, 146(12), 04020143.

Abdelkhalek, S., & Zayed, T. (2020). Simulation-based planning of concrete bridge deck inspection with non-destructive technologies. Auto-mation in Construction, 119, 103337.

AbouRizk, S., Halpin, D., Mohamed, Y., & Hermann, U. (2011). Research in modeling and simulation for improving construction engineering operations. Journal of Construction Engineering and Management, 137(10), 843-852.

AbouRizk, S. (2010). Role of simulation in construction engineering and management. Journal of construction engineering and management, 136(10), 1140-1153.

Afifi, M., Fotouh, A., Al-Hussein, M., & Abourizk, S. (2020). Integrated lean concepts and continuous/discrete-event simulation to examine productivity improvement in door assembly-line for residential buildings. International Journal of Construction Management, 1-12.

Ahn, S., & Lee, S. (2015). Methodology for creating empirically supported agent-based simulation with survey data for studying group behav-ior of construction workers. Journal of Construction Engineering and Management, 141(1), 04014065.

Akhavian, R., & Behzadan, A. H. (2018). Coupling human activity recognition and wearable sensors for data-driven construction simulation. J. Inf. Technol. Constr., 23(1), 1-15.

Akhavian, R., & Behzadan, A. H. (2014). Evaluation of queuing systems for knowledge-based simulation of construction processes. Automa-tion in Construction, 47, 37-49.

Al-Emran, A., Kapur, P., Pfahl, D., & Ruhe, G. (2010). Studying the impact of uncertainty in operational release planning–An integrated meth-od and its initial evaluation. Information and Software Technology, 52(4), 446-461.

Alvanchi, A., Azimi, R., Lee, S., AbouRizk, S. M., & Zubick, P. (2012a). Off-site construction planning using discrete event simulation. Jour-nal of Architectural Engineering, 18(2), 114-122.

Alvanchi, A., Lee, S., & AbouRizk, S. (2012b). Dynamics of working hours in construction. Journal of Construction Engineering and Man-agement, 138(1), 66-77.

Alvanchi, A., Lee, S., & AbouRizk, S. M. (2012c). Dynamics of workforce skill evolution in construction projects. Canadian Journal of Civil Engineering, 39(9), 1005-1017.

Alvanchi, A., Lee, S., & AbouRizk, S. (2011). Modeling framework and architecture of hybrid system dynamics and discrete event simulation for construction. Computer‐Aided Civil and Infrastructure Engineering, 26(2), 77-91.

Arashpour, M., & Arashpour, M. (2015). Analysis of workflow variability and its impacts on productivity and performance in construction of multistory buildings. Journal of Management in Engineering, 31(6), 1-9.

Arashpour, M., Wakefield, R., Blismas, N., & Lee, E. (2014). Analysis of disruptions caused by construction field rework on productivity in residential projects. Journal of construction engineering and management, 140(2), 1-12.

Araya, F. (2022). Modeling the influence of multiskilled construction workers in the context of the covid-19 pandemic using an agent-based ap-proach. Revista de la Construcción. Journal of Construction, 21(1), 105-117.

Araya, F. (2020). Agent based modeling: a tool for construction engineering and management?. Revista Ingeniería de Construcción, 35(2), 111-118.

Athigakunagorn, N., & Limsawasd, C. (2020). Effective Crew Allocation Using Discrete-Event Simulation: Building Scaffolding Case Study in Thailand. Engineering Journal, 24(4), 143-156.

Aziz, Z., Qasim, R. M., & Wajdi, S. (2017). Improving productivity of road surfacing operations using value stream mapping and discrete event simulation. Construction innovation.

Baniassadi, F., Alvanchi, A., & Mostafavi, A. (2018). A simulation-based framework for concurrent safety and productivity improvement in construction projects. Engineering, Construction and Architectural Management.

Beißert, U., König, M., & Bargstädt, H. J. (2010). Soft Constraint-based simulation of execution strategies in building engineering. Journal of simulation, 4(4), 222-231.

Bokor, O., Florez, L., Osborne, A., & Gledson, B. J. (2019). Overview of construction simulation approaches to model construction process-es. Organization, Technology and Management in Construction: an International Journal, 11(1), 1853-1861.

Bohács, G., Gáspár, D., Kádár, B., & Pfeiffer, A. (2016). Simulation support in construction uncertainty management: A production modelling approach. Periodica Polytechnica Transportation Engineering, 44(2), 115-122.

Brodetskaia, I., Sacks, R., & Shapira, A. (2013). Stabilizing production flow of interior and finishing works with reentrant flow in building construction. Journal of construction engineering and management, 139(6), 665-674.

Cabrera, A.G. (2010). Simulation of constructive processes. Revista ingeniería de construcción, 25(1), 121-141.

Chen, S., Lu, W., Olofsson, T., Dehghanimohammadabadi, M., Emborg, M., Nilimaa, J., ... & Feng, K. (2020a). Concrete Construction: How to Explore Environmental and Economic Sustainability in Cold Climates. Sustainability, 12(9), 3809.

Chen, Q., Adey, B. T., Haas, C., & Hall, D. M. (2020b). Using look-ahead plans to improve material flow processes on construction projects when using BIM and RFID technologies. Construction innovation, 20(3), 471-508.

Chen, H. M., & Huang, P. H. (2013). 3D AR-based modeling for discrete-event simulation of transport operations in construction. Automation in construction, 33, 123-136.

Cheng, J. C., Tan, Y., Song, Y., Mei, Z., Gan, V. J., & Wang, X. (2018). Developing an evacuation evaluation model for offshore oil and gas platforms using BIM and agent-based model. Automation in Construction, 89, 214-224.

Cheng, M. Y., & Tran, D. H. (2016). Integrating chaotic initialized opposition multiple-objective differential evolution and stochastic simula-tion to optimize ready-mixed concrete truck dispatch schedule. Journal of Management in Engineering, 32(1), 04015034.

Conrads, A., Scheffer, M., Mattern, H., König, M., & Thewes, M. (2017). Assessing maintenance strategies for cutting tool replacements in mechanized tunneling using process simulation. Journal of Simulation, 11(1), 51-61.

Corona-Suárez, G. A., AbouRizk, S. M., & Karapetrovic, S. (2014). Simulation-based fuzzy logic approach to assessing the effect of project quality management on construction performance. Journal of Quality and Reliability Engineering, 2014.

Dang, T. T., Schoesser, B., Thewes, M., & Koenig, M. (2018). Evaluation of productivities influenced by disturbances and different soil compositions in microtunnelling using process simulation. Tunnelling and Underground Space Technology, 76, 10-20.

Dallasega, P., Rojas, R. A., Bruno, G., & Rauch, E. (2019). An agile scheduling and control approach in ETO construction supply chains. Computers in Industry, 112, 103122.

de Freitas, J.G. and Costa, H.G. (2017), "Impacts of Lean Six Sigma over organizational sustainability: A systematic literature review on Sco-pus base", International Journal of Lean Six Sigma, Vol. 8 No. 1, pp. 89-108. https://doi.org/10.1108/IJLSS-10-2015-0039

Du, J., El-Gafy, M., & Zhao, D. (2016). Optimization of change order management process with object-oriented discrete event simulation: Case study. Journal of Construction Engineering and Management, 142(4), 05015018.

ElNimr, A., Fagiar, M., & Mohamed, Y. (2016). Two-way integration of 3D visualization and discrete event simulation for modeling mobile crane movement under dynamically changing site layout. Automation in construction, 68, 235-248.

Fayed, R. A., & Samer Ezeldin, A. (2018). Simulation and optimization model for electrical substation construction. Journal of Information Technology in Construction, 23, 215.

Feng, K., Lu, W., Chen, S., & Wang, Y. (2018). An integrated environment–cost–time ptimization method for construction contractors considering global warming. Sustainability, 10(11), 4207.

Feng, K., Lu, W., Olofsson, T., Chen, S., Yan, H., & Wang, Y. (2018). A predictive environmental assessment method for construction opera-tions: Application to a Northeast China case study. Sustainability, 10(11), 3868.

Frough, O., Khetwal, A., & Rostami, J. (2019). Predicting TBM utilization factor using discrete event simulation models. Tunnelling and un-derground space technology, 87, 91-99.

Goh, Y. M., & Ali, M. J. A. (2016). A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study. Accident Analysis & Prevention, 93, 310-318.

Golabchi, A., Han, S., AbouRizk, S., & Kanerva, J. (2016). Micro-motion level simulation for efficiency analysis and duration estimation of manual operations. Automation in Construction, 71, 443-452.

Golzarpoor, H., González, V., Shahbazpour, M., & O’Sullivan, M. (2017). An input-output simulation model for assessing production and environmental waste in construction. Journal of cleaner production, 143, 1094-1104.

González, V., & Echaveguren, T. (2012). Exploring the environmental modeling of road construction operations using discrete-event simula-tion. Automation in Construction, 24, 100-110.

Gurevich, U., & Sacks, R. (2014). Examination of the effects of a KanBIM production control system on subcontractors' task selections in interior works. Automation in construction, 37, 81-87.

Han, S., Lee, S., & Pena-Mora, F. (2012). Identification and quantification of non-value-adding effort from errors and changes in design and construction projects. Journal of Construction Engineering and Management, 138(1), 98-109.

Hassan, N. M., Al Maazmi, T., Al Hadhrami, A., & Al Hosani, M. (2016). Discrete event simulation: a vital tool for a concurrent life cycle design. Construction Innovation.

Heravi, G., & Firoozi, M. (2017). Production process improvement of buildings’ prefabricated steel frames using value stream mapping. The International Journal of Advanced Manufacturing Technology, 89(9), 3307-3321.

Hu, D., Mohamed, Y., Taghaddos, H., & Hermann, U. (2018). A simulation-based method for effective workface planning of industrial con-struction projects. Construction Management and Economics, 36(6), 328-347.

Hu, D., & Mohamed, Y. (2014). Simulation-model-structuring methodology for industrial construction fabrication shops. Journal of construc-tion engineering and management, 140(5), 04014002.

Hwang, S., Park, M., Lee, H. S., & Lee, S. (2016). Hybrid simulation framework for immediate facility restoration planning after a catastrophic disaster. Journal of Construction Engineering and Management, 142(8), 04016026.

Hwang, S., Park, M., Lee, H. S., Lee, S., & Kim, H. (2015). Postdisaster interdependent built environment recovery efforts and the effects of governmental plans: Case analysis using system dynamics. Journal of construction engineering and management, 141(3), 04014081.

Jiang, T., An, X., Minchin Jr, R. E., & Li, S. (2016). Application of discrete-event simulation in the quantitative evaluation of information systems in infrastructure maintenance management processes. Journal of Management in Engineering, 32(2), 05015008.

Jung, M., Park, M., Lee, H. S., & Chi, S. (2018). Multimethod supply chain simulation model for high-rise building construction projects. Journal of Computing in Civil Engineering, 32(3), 04018007.

Jung, M., Park, M., Lee, H. S., & Kim, H. (2016). Weather-delay simulation model based on vertical weather profile for high-rise building construction. Journal of construction engineering and management, 142(6), 04016007.

Karimidorabati, S., Haas, C. T., & Gray, J. (2016). Evaluation of automation levels for construction change management. Engineering, con-struction and architectural management.

Khan, M. A., Deep, S., Asim, M., & Khan, Z. R. (2017). Quantization of risks involved in supply of ready mix concrete in construction in-dustry in Indian scenario. International Journal of Civil Engineering and Technology, 8(3), 175-184.

Khanh, H. D., & Kim, S. Y. (2020). Exploring Productivity of Concrete Truck for Multistory Building Projects Using Discrete Event Simula-tion. KSCE Journal of Civil Engineering, 24(12), 3531-3545.

Khodabandelu, A., & Park, J. (2021). Agent-based modeling and simulation in construction. Automation in Construction, 131, 103882.

Kim, K., & Kim, K. J. (2010). Multi-agent-based simulation system for construction operations with congested flows. Automation in Con-struction, 19(7), 867-874.

Kim, T. and Kim, Y-W. (2016) Process Improvement using Activity-Based Costing. Lean Construction Journal 2016 pp 25-34

Kisi, K. P., Mani, N., Rojas, E. M., & Foster, E. T. (2017). Optimal productivity in labor-intensive construction operations: Pilot study. Jour-nal of Construction Engineering and Management, 143(3), 04016107.

Krantz, J., Feng, K., Larsson, J., & Olofsson, T. (2019). ‘Eco-Hauling’principles to reduce carbon emissions and the costs of earthmoving-A case study. Journal of Cleaner Production, 208, 479-489.

Krantz, J., Larsson, J., Lu, W., & Olofsson, T. (2015). Assessing embodied energy and greenhouse gas emissions in infrastructure projects. Buildings, 5(4), 1156-1170.

Larsson, J., Lu, W., Krantz, J., & Olofsson, T. (2016). Discrete event simulation analysis of product and process platforms: A bridge con-struction case study. Journal of Construction Engineering and Management, 142(4), 04015097.

Larsson, R., & Rudberg, M. (2019). Impact of weather conditions on in situ concrete wall operations using a simulation-based approach. Journal of construction engineering and management, 145(7)

Lau, S. C., Lu, M., & Poon, C. S. (2014). Formalized approach to discretize a continuous plant in construction simulations. Journal of con-struction engineering and management, 140(8), 04014032.

Lee, J., Park, M., Lee, H. S., & Hyun, H. (2019). Classification of modular building construction projects based on schedule-driven approach. Journal of Construction Engineering and Management, 145(5), 04019031.

Lee, D. E., Yi, C. Y., Lim, T. K., & Arditi, D. (2010). Integrated simulation system for construction operation and project scheduling. Journal of computing in civil engineering, 24(6), 557-569.

Leite, F., Cho, Y., Behzadan, A. H., Lee, S., Choe, S., Fang, Y., ... & Hwang, S. (2016). Visualization, information modeling, and simulation: Grand challenges in the construction industry. Journal of Computing in Civil Engineering, 30(6), 04016035.

Li, C. Z., Hong, J., Fan, C., Xu, X., & Shen, G. Q. (2018). Schedule delay analysis of prefabricated housing production: A hybrid dynamic approach. Journal of cleaner production, 195, 1533-1545.

Li, H. X., Zhang, L., Mah, D., & Yu, H. (2017). An integrated simulation and optimization approach for reducing CO2 emissions from on-site construction process in cold regions. Energy and buildings, 138, 666-675.

Limsawasd, C., & Athigakunagorn, N. (2017). An application of discrete-event simulation in estimating emissions from equipment operations in flexible pavement construction projects. Engineering Journal, 21(7), 197-211.

Lindhard, S. M., Hamzeh, F., Gonzalez, V. A., Wandahl, S., & Ussing, L. F. (2019). Impact of activity sequencing on reducing variability. Journal of Construction Engineering and Management, 145(3), 04019001.

Linnenluecke, M. K., Marrone, M., & Singh, A. K. (2020). Conducting systematic literature reviews and bibliometric analyses. Australian Journal of Management, 45(2), 175-194.

Liu, H., Altaf, M. S., Lei, Z., Lu, M., & Al-Hussein, M. (2015). Automated production planning in panelized construction enabled by integrat-ing discrete-event simulation and BIM. In Proceedings, International Construction Specialty Conference (Vol. 48, pp. 1-10).

Longman, M., & Miles, S. B. (2019). Using discrete event simulation to build a housing recovery simulation model for the 2015 Nepal earth-quake. International Journal of Disaster Risk Reduction, 35, 101075.

Louis, J., & Dunston, P. S. (2017). Methodology for real-time monitoring of construction operations using finite state machines and discrete-event operation models. Journal of construction engineering and management, 143(3), 04016106.

Lu, W., & Olofsson, T. (2014). Building information modeling and discrete event simulation: Towards an integrated framework. Automation in construction, 44, 73-83.

Macal, C & North, M. (2010) Tutorial on agent-based modelling and simulation, Journal of Simulation, 4:3, 151-162, DOI: 10.1057/jos.2010.3

Martinez, J. C. (2010). Methodology for conducting discrete-event simulation studies in construction engineering and management. Journal of Construction Engineering and Management, 136(1), 3-16.

Matejević, B., Zlatanović, M., & Cvetković, D. (2018). The simulation model for predicting the productivity of the reinforced concrete slabs concreting process. Tehnički vjesnik, 25(6), 1672-1679.

Mawlana, M., Vahdatikhaki, F., Doriani, A., & Hammad, A. (2015). Integrating 4D modeling and discrete event simulation for phasing evalua-tion of elevated urban highway reconstruction projects. Automation in construction, 60, 25-38.

Montaser, A., & Moselhi, O. (2014). Truck+ for earthmoving operations. Journal of Information Technology in Construction (ITcon), 19(25), 412-433.

Moradi, S., Nasirzadeh, F., & Golkhoo, F. (2017). Modeling labor productivity in construction projects using hybrid SD-DES approach. Sci-entia Iranica, 24(6), 2752-2761.

Moradi, S., Nasirzadeh, F., & Golkhoo, F. (2015). A hybrid SD–DES simulation approach to model construction projects. Construction inno-vation.

Nadoushani, Z. S. M., Akbarnezhad, A., & Rey, D. (2018). Optimization of concrete placing operation based on competing carbon footprint, cost and production rate objectives. Engineering, Construction and Architectural Management.

Nassar, K. (2010). Queuing Model for Assessing the Efficiency of Building Corridors. Journal of architectural engineering, 16(1), 3-10.

Osman, H. (2012). Agent-based simulation of urban infrastructure asset management activities. Automation in Construction, 28, 45-57.

Osman, H., Ammar, M., & El-Said, M. (2017). Optimal scheduling of water network repair crews considering multiple objectives. Journal of Civil Engineering and Management, 23(1), 28-36.

Sandoval, C. A. O., Tizani, W., & Koch, C. (2018). A method for discrete event simulation and building information modelling integration using a game engine. Advances in Computational Design, 3(4), 405-418.

Peña-Mora, F., Han, S., Lee, S., & Park, M. (2008). Strategic-operational construction management: Hybrid system dynamics and discrete event approach. Journal of Construction Engineering and Management, 134(9), 701-710.

Puri, V., & Martinez, J. C. (2013). Modeling of simultaneously continuous and stochastic construction activities for simulation. Journal of construction engineering and management, 139(8), 1037-1045.

Rekapalli, P. V., & Martinez, J. C. (2011). Discrete-event simulation-based virtual reality environments for construction operations: Technolo-gy introduction. Journal of Construction Engineering and Management, 137(3), 214-224.

Sacks, R., Gurevich, U., & Belaciano, B. (2015). Hybrid discrete event simulation and virtual reality experimental setup for construction management research. Journal of Computing in Civil Engineering, 29(1), 04014029.

Sadeghi, N., Fayek, A. R., & Gerami Seresht, N. (2016). A fuzzy discrete event simulation framework for construction applications: Improv-ing the simulation time advancement. Journal of Construction Engineering and Management, 142(12), 04016071.

Sadeghi, N., Fayek, A. R., & Seresht, N. G. (2015). Queue performance measures in construction simulation models containing subjective uncertainty. Automation in Construction, 60, 1-11.

Sadeghi, N., Fayek, A. R., & Ingolfsson, A. (2012). Simulation-based approach for estimating project completion time of stochastic resource–constrained project networks. Journal of computing in civil engineering, 26(4), 558-560.

Seo, J., Lee, S., & Seo, J. (2016). Simulation-based assessment of workers’ muscle fatigue and its impact on construction operations. Journal of Construction Engineering and Management, 142(11), 04016063.

Shawki, K. M., Kilani, K., & Gomaa, M. A. (2015). Analysis of earth-moving systems using discrete-event simulation. Alexandria Engineer-ing Journal, 54(3), 533-540.

Shin, Y., Cho, H., & Kang, K. I. (2011). Simulation model incorporating genetic algorithms for optimal temporary hoist planning in high-rise building construction. Automation in construction, 20(5), 550-558.

V.K. Singh, P. Singh, M. Karmakar, J. Leta, P. Mayr, The journal coverage of Web of Science, Scopus and Dimensions: a comparative analy-sis, Scientometrics 126 (6) (2021) 5113–5142, https://doi.org/10.1007/s11192-021-03948-5.

Sneha, K., & Tezeswi, T. P. (2016). A Comparative Study of Construction Using Schnell Concrewall® pre-cast sandwich composite panel and RC moment frame with brick infill. Int. J. Civ. Eng. Technol, 7, 110.

Sterman, J. (2000). Business dynamics: System thinking and modeling for a complex world, McGraw-Hill, New York.

Vidalakis, C., Tookey, J. E., & Sommerville, J. (2013). Demand uncertainty in construction supply chains: a discrete event simulation study. Journal of the Operational Research Society, 64(8), 1194-1204.

Wang, Z., Hu, H., & Gong, J. (2018). Framework for modeling operational uncertainty to optimize offsite production scheduling of precast components. Automation in Construction, 86, 69-80.

Weiszer, M., Fedorko, G., Molnár, V., Tučková, Z., & Poliak, M. (2020). Dispatching policy evaluation for transport of ready mixed concrete. Open Engineering, 10(1), 120-128.

Wickramasekara, A. N., Gonzalez, V., O’Sullivan, M., Walker, C., Poshdar, M., & Ying, F. (2020, August). Exploring the Integration of Last Planner® System, Bim, and Construction Simulation. In Annual Conference of the International. Group for Lean Construction.

Xu, X., Wang, J., Li, C. Z., Huang, W., & Xia, N. (2018). Schedule risk analysis of infrastructure projects: A hybrid dynamic approach. Au-tomation in Construction, 95, 20-34.

Younes, T., Ni, F. M. W., & Tighe, S. (2020). Risk analysis in paving operations using discrete event simulation: a case study of Taiwan permeable asphalt concrete pavement pilot road project. International Journal of Pavement Engineering, 21(7), 830-840.

Yu, B., Meng, X., & Liu, Q. (2020). Multi-objective optimisation of hot in-place recycling of asphalt pavement considering environmental impact, cost and construction quality. International Journal of Pavement Engineering, 21(13), 1576-1584.

Yuan, Z., Qiao, Y., Guo, Y., Wang, Y., Chen, C., & Wang, W. (2020). Research on lean planning and optimization for precast component production based on discrete event simulation. Advances in Civil Engineering, 2020.

Zankoul, E., & Khoury, H. (2016). Modeling, animating, and optimizing on-shore wind farm construction operations. Journal of Computing in Civil Engineering, 30(6), 05016001.

Zankoul, E., Khoury, H., & Awwad, R. (2015). Evaluation of agent-based and discrete-event simulation for modeling construction earthmov-ing operations. In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 32, p. 1). IAARC Publications

Zhang, H. (2015a). Discrete-event simulation for estimating emissions from construction processes. Journal of Management in Engineering, 31(2), 04014034.

Zhang, H. (2015b). Simulation-based estimation of fuel consumption and emissions of asphalt paving operations. Journal of Computing in Civil Engineering, 29(2), 04014039.

Zhang, Y., AbouRizk, S. M., Xie, H., & Moghani, E. (2012). Design and implementation of loose-coupling visualization components in a distributed construction simulation environment with HLA. Journal of Computing in Civil Engineering, 26(2), 248-258.

Denghua, Z., Haifeng, Z., and Bo, C. (2015). Study on construction simulation for roller compaction of dam with asphalt concrete core based on real-time monitoring. Journal of Hydroelectric Engineering, 34(7), 118-126.

Zhong Denghua, Zhang Qinya, Du Rongxiang,.Tong Dawei, Shi Zhichao. (2015). Dynamic Construction Simulation of Core Rock-Fill Dam Based on CATIA Platform. Journal of Tianjin University (Science and Technology). Vol.48 No.12. Dec. 2015, in Chinese.

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2022-08-31

How to Cite

Araya, F. (2022). Integration of discrete event simulation with other modeling techniques to simulate construction engineering and management: an overview. Revista De La Construcción. Journal of Construction, 21(2), 338–353. https://doi.org/10.7764/RDLC.21.2.338