مدل سازی عامل محور و یکپارچه سازی رویکردهای شبیه سازی پویایی سیستم

نویسنده

گروه مهندسی عمران، دانشکده فنی و مهندسی، موسسه آموزش عالی عمران و توسعه، همدان، ایران

چکیده

مقدار بهره‌وری در پروژه های ساخت از یکسو تحت تأثیر فاکتورهای مختلف با رفتار پیوسته در طول زمان بوده و از سوی دیگر تحت تأثیر تعامل و اندرکنش موجود بین نیروی انسانی حاضر در پروژه می‌باشد. در این تحقیق با استفاده از یکپارچه‌سازی روش شبیه‌سازی پویایی سیستمی و روش مدلسازی عامل‌محور، ابزاری نوین برای مدل‌سازی و پیش‌بینی بهره‌وری در پروژه‌های ساخت ارائه می‌گردد. استفاده از روش شبیه‌سازی ترکیبی پویایی سیستم و مدلسازی عامل‌محور ما را قادر می‌سازد انواع عوامل مؤثر بر بهره‌وری را به صورت همزمان در نظر بگیریم. در این تحقیق کلیه عوامل و فاکتورهای اثرگذار که دارای رفتاری پیوسته در طول زمان می باشند با استفاده از روش شبیه‌سازی پویایی سیستم مدلسازی خواهند شد. در ادامه برای درنظرگیری تأثیر تعاملات بین نیروی انسانی حاضر در پروژه بر روی بهره‌وری، از رویکرد مدلسازی عامل‌محور استفاده شده است. در نهایت با ترکیب و یکپارچه سازی دو مدل شبیه‌سازی پویایی سیستم و مدلسازی عامل محور، مدلی ترکیبی برای پیش‌بینی میزان بهره‌وری با در نظر داشتن کلیه عوامل اثرگذار ارایه می گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Agent-based modeling and integration of system dynamics simulation approaches

نویسنده [English]

  • Kiana Ahghari
Department of Civil Engineering, Faculty of Technology & Engineering, University College of Omran & Tosseeh, Hamedan, Iran.
چکیده [English]

On the one hand, the amount of productivity in construction projects is influenced by different factors with continuous behavior over time, and on the other hand, by the interaction and interaction between the human resources present in the project. In this research a new tool for modeling and predicting productivity in construction projects is presented by integrating the system dynamics simulation method and agent-based modeling method. Using a combination of system dynamics simulation and agent-based modeling enables us to consider a variety of factors affecting productivity simultaneously. In this research, all the effective factors and factors that have continuous behavior over time will be modeled using system dynamics simulation. In the following, factor-based modeling approach is used to consider the effect of the interactions between the manpower present in the project on productivity. Finally, by combining and integrating the two systems of system dynamics simulation and agent-based modeling, a hybrid model for predicting the productivity with all the effective factors is presented.

کلیدواژه‌ها [English]

  • Productivity
  • Combined Simulation
  • System Dynamic Simulation
  • Agent-Based Modeling
  1. Song, L. and AbouRizk, S.M. "Measuring and modeling labor productivity using historical data", Constr. Eng. M., 134(10), pp. 786-794 (2008).
  2. Ezeldin, A.S. and Sharara, L.M. "Neural networks for estimating the productivity of concreting activities", J. Constr. Eng. M., 132(6), pp. 650-656 (2006).
  3. Zayed, T.M. and Halpin, D.W. "Pile construction productivity assessment", Constr. Eng. M., 131(6), pp. 705-714 (2005).
  4. Gerek, I.H., Erdis, E., Mistikoglu, G. and Usmen, M. "Modelling masonry crew productivity using two artificial neural network techniques" Civ. Eng. Manag., 21(2), pp. 231-238 (2015).
  5. Poirier, E.A., Staub-French, S. and Forgues, D. "Measuring the impact of BIM on labor productivity in a small specialty contracting enterprise through action-research", Constr., 58, pp. 74-84 (2015).
  6. Kisi, K.P., Mani, N. and Rojas, E.M. " Estimating Optimal Labor Productivity: A Two-Pronged Strategy", Res. Cong., ASCE, pp. 757-766 (2014).
  7. Mani, N., Kisi, K.P. and Rojas, E.M. " Estimating labor productivity frontier: a pilot study", Res. Cong., ASCE, pp. 807-816 (2014).
  8. Jarkas, A.M. " Influence of buildability factors on rebar installation labor productivity of columns", Constr. Eng. M., 138(2), pp. 258-267 (2012).
  9. Arashpour, M. and Arashpour, M. " Analysis of Workflow Variability and Its Impacts on Productivity and Performance in Construction of Multistory Buildings", Manage. Eng., 31(6), (2015).
  10. Ibbs, W., Nguyen, L.D. and Lee, S. "Quantified impacts of project change" J. Prof. Iss. Eng. Ed. Pr., 133(1), pp. 45-52 (2007).
  11. Goodrum, P.M., Zhai, D. and Yasin, M.F. "Relationship between changes in material technology and construction productivity" Constr. Eng. M., 135(4), pp. 278-287, (2009).
  12. Watkins, M., Mukherjee, A., Onder, N. and Mattila, K. "Using agent-based modeling to study construction labor productivity as an emergent property of individual and crew interactions", Constr. Eng. M., 135(7), pp. 657-667 (2009).
  13. Mawdesley, M.J. and Al-Jibouri, S. "Modelling construction project productivity using systems dynamics approach", J. Prod. Perf. Manag., 59(1), pp. 18-36 (2009).
  14. Nasirzadeh, F. and Nojedehi, P. "Dynamic modeling of labor productivity in construction projects", J. Proj. Manag., 31(6), pp. 903-911 (2013).
  15. Schieritz, N. and Milling, P.M. "Modeling the forest or modeling the trees", 21st Int. Conf. Syst. Dyn. Soc., (2003).
  16. Wu, D.D., Kefan, X., Hua, L., Shi, Zh. and Olson, D.L. "Modeling technological innovation risks of an entrepreneurial team using system dynamics: an agent-based perspective" Forcast. Soc., 77(6), pp. 857-869 (2010).
  17. Schieritz, N. and Grobler, A. "Emergent structures in supply chains-a study integrating agent-based and system dynamics modeling" 36th Int. Conf. Syst. Sci., IEEE, Hawaii (2003).
  18. Nasirzadeh, F., Khanzadi, M. and Afshar, A. "Simulating consequences of concurrent risks on project time and cost by considering uncertanities" Sharif Journal, Civil Engineering, 30(2), pp. 69-75, (2014).
  19. Nasirzadeh, F. "An integrated fuzzy system dynamics approach to construction project risk management" Doctoral thesis, Iran University of Science and Technology (2008).
  20. Nasirzadeh, F., Afshar, and Khanzadi, M. "Dynamic risk analysis in construction projects" Can. J. Civ. Eng., 35(8), pp. 820-831 (2008).
  21. Barbati, M., Bruno, G. and Genovese, A. "Applications of agent-based models for optimization problems: A literature review", Syst. Appl., 39(5), pp. 6020-6028 (2012).
  22. Osman, H., "Agent-based simulation of urban infrastructure asset management activities", Constr., 28, pp. 45-57 (2012).
  23. Macal, C.M. and North, M.J. "Agent-based modeling and simulation: ABMS examples", 40th Winter Simulation Conference (2008).
  24. Sawhney, A., Bashford, H., Walsh, K. and Mulky, A.R. "Agent-based modeling and simulation in construction", Sim. Conf., Winter, IEEE (2003).
  25. Epstein, M. and Axtell, R. "Growing artificial societies: Social science from the ground up", Boston, MA, MIT Press (1996).
  26. Lättilä, L., Hilletofth, P. and Lin, B. "Hybrid simulation models–when, why, how? ", Syst. Appl., 37(12), pp. 7969-7975 (2010).
  27. Hilletofth, P., Aslam, T., and Hilmola, O. P. "Multi-agent-based supply chain management: a case study of requisites", IJNVO, 7(2), pp. 184-206 (2010).
  28. Lorenz, T. and Jost, A. "Toward an orientation framework in multi-paradigm modeling" 24th Int. Conf. Syst. Dyn. Soc. (2006).
  29. Swinerd, C. and McNaught, K.R. "Design classes for hybrid simulations involving agent-based and system dynamics models", Model. Pract. Th., 25, pp. 118-133 (2012).
  30. Mostafavi, A., Abraham, D., Delaurentis, D., Sinfield, J. and Queiroz, C. "Innovation Policy Assessment for Civil Infrastructure System-of-Systems" Res. Cong., Construction Challenges in a Flat World, ASCE (2012).
  31. Duggan, J. "A Simulator for Continous Agent-Based Modelling", 26th Int. Conf. Syst. Dyn. Soc. (2008).
  32. Horner, R. and Talhouni, B. "Effects of accelerated working, delays and disruption on labour productivity", Chartered Institute of Building (1993).
  33. Thomas, H. and Smith, G." Loss of labor productivity: The weight of expert opinion", PTI Rep, 9019 (1992).
  34. Thomas, H.R., Riley, D.R. and Sinha, S.K. "Fundamental principles for avoiding congested work areas—A case study", Period. Struct. Des. Constr., 11(4), pp. 197-205 (2006)