Abstract
Effective construction waste management (CWM) is a key challenge for global sustainable development. In particular, scientific transportation management of municipal construction waste (CW) is also an important way to reduce environmental pressure due to the scarcity of land resources and the lack of landfill facilities in most cities. Based on the hybrid simulation method, this paper implements dynamic regulations and analyzes the effects of different construction waste management policies by applying agent based modeling (ABM) simulation method, and designs transportation plans by loading geographic information system (GIS) data. Construction waste transportation in Shenzhen is taken as an example in which GIS and other required excel data are loaded into AnyLogic simulation software. According to the ABM simulation results, the optimal disposal route of CW transportation is identified. Simulation results show that this method can effectively provide regular path planning for waste transportation, and follow the transportation route stipulated by the traffic regulations of Shenzhen. The findings can also provide a guide for decision making of CW transportation plans.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zheng, L., Wu, H., Zhang, H., Duan, H., Wang, J., Jiang, W., Dong, B., Liu, G., Zuo, J., & Song, Q. (2017). Characterizing the generation and flows of construction and demolition waste in China. Construction and Building Materials, 136, 405–413.
Huang, B., Wang, X., Kua, H., Geng, Y., Bleischwitz, R., & Ren, J. (2018). Construction and demolition waste management in China through the 3R principle. Resources, Conservation and Recycling, 129, 36–44.
Yuan, H. P., & Shen, L. Y. (2011). Trend of the research on construction and demolition waste management. Waste Management, 31, 670–679.
Shenzhen Government. Shenzhen municipal construction waste transportation and disposal management measures [EB/OL] (2014–01–02) [2020.3.6]. http://www.sz.gov.cn/cn/xxgk/zfxxgj/zcfg/szsfg/content/post_6581635.html.
Das, S., & Bhattacharyya, B. K. (2015). Optimization of municipal solid waste collection and transportation routes. Waste Management, 43, 9–18.
Parkitny, W. (2017). Optimization of logistics of municipal waste transport in regional formulation. In: 17th International Multidisciplinary Scientific Geoconference, SGEM 2017 (pp. 131–138), November 27, 2017–November 29, 2017, Vienna, Austria.
Weiwei, G., Lingyun, Z., & Fei, Y. (2019). Multi-agent GIS simulation for railway logistics optimization. In 2019 4th International Conference on Intelligent Transportation Engineering (ICITE) (pp. 64–68).
Khanh, N. T., Anh, N. T. N., Doanh, N. N., Van, D. T. H. (2017). Optimization of municipal solid waste transportation by integrating GIS analysis, equation-based, and agent-based model. Waste Management, 59, 14–22.
Gan, V. J. L., Cheng, J. C. P. (2015). Formulation and analysis of dynamic supply chain of backfill in construction waste management using agent-based modeling. Advanced Engineering Informatics, 29, 878–888.
Ren, Z., Anumba, C. J. (2004). Multi-agent systems in construction-state of the art and prospects. Automation in Construction, 13, 421–434.
Van Groningen, C. N., Braun, M. D., Craig, B. A., Olson, C. M., Simunich, K. L. (2010). The Logistics Process Analysis Tool (LPAT): Combining agent-based and discrete event simulation techniques for improved logistics analysis. In Summer Computer Simulation Conference, SCSC 2010, Part of the 2010 Summer Simulation Multiconference, SummerSim 2010 (pp. 154–159), July 12, 2010–July 14, 2010, Ottawa, ON, Canada.
Akanle, O. M., & Zhang, D. Z. (2008). Agent-based model for optimising supply-chain configurations. International Journal of Production Economics, 115, 444–460.
Kiomjian, D., Srour, F.J., Srour, I. (2018). Addressing quality problems in the construction industry: An agent based modelling approach. In Construction Research Congress 2018: Construction Information Technology, CRC 2018 (pp. 632–641), April 2, 2018—April 4, 2018, American Society of Civil Engineers (ASCE), New Orleans, LA, United states.
Macal, C. M. (2011). To agent-based simulation from system dynamics. In Simulation Conference (WSC), Proceedings of the 2010 Winter. Winter Simulation Conference.
Bankes, S. C. (2002). Agent-based modeling: A revolution? Proceedings of the National Academy of Sciences, 99, 7199–7200.
Heath, B., Hill, R., & Ciarallo, F. (2009). A survey of agent-based modeling practices (January 1998 to July 2008). Journal of Artificial Societies and Social Simulation, 12, 9.
Malakahmad, A., Bakri, P. M., Mokhtar, M. R. M., Khalil, N. (2014). Solid waste collection routes optimization via GIS techniques in Ipoh city, Malaysia. Procedia Engineering, 77, 20–27. https://doi.org/10.1016/j.proeng.2014.07.023; Fourth International Symposium on Infrastructure Engineering in Developing Countries, IEDC 2013.
Minale, T. A. E. A. S. (2013). Solid waste dumping site suitability analysis using geographic information system (GIS) and remote sensing for Bahir Dar Town, North Western Ethiopia. African Journal of Environmental Science and Technology, 7, 976–989.
Irfan, M., Houdayer, B., Shah, H., Koj, A., & Thomas, H. (2019). GIS-based investigation of historic landfill sites in the coastal zones of Wales (UK). Euro-Mediterranean Journal for Environmental Integration, 4, 10.
Nguyen, M. H., Nguyen, M. S., Ho, T. V., Phan, T. H., Thi, V. A. T. (2013). Dynamic path optimization in traffic routing. Asian simulation and modeling (p. 4351). Mahidol University.
Huang, S.-H., & Lin, P.-C. (2015). Vehicle routing–scheduling for municipal waste collection system under the “Keep Trash off the Ground” policy. Omega, 55, 24–37.
Darbandsari, P., Kerachian, R., & Malakpour-Estalaki, S. (2017). An Agent-based behavioral simulation model for residential water demand management: The case-study of Tehran, Iran. Simulation Modelling Practice and Theory, 78, 51–72.
Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99, 7280–7287.
Chollima Bidding Network. Bidding Information Platform [EB/OL]. (2019). http://www.qianlima.com/common/nzj_index_search.jsp?leixing=sy.
Shenzhen Government. Shenzhen Government Open data platform [EB/OL](2019–11–05). https://opendata.sz.gov.cn/data/dataSet/toDataDetails/29200_01003566.
Acknowledgements
This research is funded by the National Nature Science Foundation of China (Grant No.71974132), the Natural Science Foundation of Guangdong Province, China (Grant No. 2018A0303130037), Shenzhen Government Nature Science Foundation (Grant No. JCYJ20190808115809385).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Cao, X., Ding, Z. (2021). Management of Municipal Construction Waste Transportation by Integrating ABM and GIS Model: A Case Study of Shenzhen. In: Lu, X., Zhang, Z., Lu, W., Peng, Y. (eds) Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate. CRIOCM 2020. Springer, Singapore. https://doi.org/10.1007/978-981-16-3587-8_17
Download citation
DOI: https://doi.org/10.1007/978-981-16-3587-8_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-3586-1
Online ISBN: 978-981-16-3587-8
eBook Packages: Business and ManagementBusiness and Management (R0)