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contributor authorJiuping Xu; Yi Shi; Siwei Zhao
date accessioned2019-03-10T12:01:07Z
date available2019-03-10T12:01:07Z
date issued2019
identifier other%28ASCE%29CO.1943-7862.0001592.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4254655
description abstractEnvironmental 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.
publisherAmerican Society of Civil Engineers
titleReverse Logistics Network-Based Multiperiod Optimization for Construction and Demolition Waste Disposal
typeJournal Paper
journal volume145
journal issue2
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/(ASCE)CO.1943-7862.0001592
page04018124
treeJournal of Construction Engineering and Management:;2019:;Volume ( 145 ):;issue: 002
contenttypeFulltext


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