Reverse Logistics Network-Based Multiperiod Optimization for Construction and Demolition Waste Disposal
Publication: Journal of Construction Engineering and Management
Volume 145, Issue 2
Abstract
Environmental pollution and resource consumption caused by construction and demolition waste (CDW) have become increasingly serious. As a result, it is urgent to focus on waste recycling, resource conservation, and environmental protection. To reduce environmental pollution and decrease waste disposal costs, this paper employs a reverse logistics network (RLN)-based multiperiod optimization for CDW recycling and disposal. To optimize the CDW disposal process, a dynamic mixed-integer linear programming (MILP) model is proposed to determine the optimal solutions. By making decisions about the disposal process and CDW disposal volumes, the overall network costs are controlled on the premise of protecting the environment. A case study from China is then introduced to demonstrate the effectiveness and efficiency of the proposed MILP model in selecting the disposal processes, determining waste disposal volumes, and controlling total costs. Scenario analyses for the collection and recycling ratios are conducted, and the influence of the government’s green tax is considered. Finally, practical policy suggestions are given to guide CDW disposal. The main contribution of this paper is that the learned CDW disposal network could strictly and efficiently regulate CDW recycling and provide a valid political instrument to dispose of CDW that can not only reduce environmental damage and construction activity resource consumption, but also convert the CDW into new construction materials to economically benefit the construction industries.
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Data Availability Statement
All data generated or analyzed during the study are included in the published paper. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
Acknowledgments
This research was supported by Chinese Universities Scientific Fund (Grant No. 2010SCU22009), Scientific Research 344 Staring Foundation of Sichuan University (Grant No. 2015SCU11034), and the National Natural Science Foundation (Grant No. 71601134).
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Published In
Journal of Construction Engineering and Management
Volume 145 • Issue 2 • February 2019
Copyright
©2018 American Society of Civil Engineers.
History
Received: Nov 24, 2017
Accepted: Jul 26, 2018
Published online: Nov 23, 2018
Published in print: Feb 1, 2019
Discussion open until: Apr 23, 2019
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