Optimisation of waste clean-up after large-scale disasters

•Included demolition operation in the two-stage disaster waste management system.•Developed MIP models which capture the key features of disaster waste clean-up.•Proposed three approaches to minimise total clean-up cost and time.•Provided thorough analysis of a case study for 2009 Black Saturday bus...

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Bibliographic Details
Published in:Waste management (Elmsford) Vol. 119; pp. 1 - 10
Main Authors: Cheng, Cheng, Zhu, Rui, Costa, Alysson M., Thompson, Russell George
Format: Journal Article
Language:English
Published: United States Elsevier Ltd 01.01.2021
Subjects:
Buildings demolition arrangement
case studies
decision making
disaster preparedness
Disaster waste clean-up
Disasters
Location selection
Mixed integer programming
Refuse Disposal
Temporary disaster waste management site
Transportation
Waste Management
wastes
Location selection
Mixed integer programming
Disaster waste clean-up
Temporary disaster waste management site
Buildings demolition arrangement
ISSN:0956-053X, 1879-2456, 1879-2456
Online Access:Get full text
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Summary:•Included demolition operation in the two-stage disaster waste management system.•Developed MIP models which capture the key features of disaster waste clean-up.•Proposed three approaches to minimise total clean-up cost and time.•Provided thorough analysis of a case study for 2009 Black Saturday bushfires.•Optimised results can help decision-maker developing the waste clean-up plan. Disaster waste clean-up after large disasters is one of the core activities at the recovery stage of disaster management, which aims to restoring the normal functioning of the disaster affected area. In this paper we considered a waste clean-up system consists of (i) demolition operation, (ii) collection of waste from customer nodes to temporary disaster waste management sites (TDWMSs), (iii) processing at TDWMSs, and (iv) transportation of the waste to final disposal sites in the recovery of disasters. A multi-objective mixed integer programming model is developed to minimise the total clean-up cost and time. Three different approaches are developed to solve the problem, which are tested with artificial instances and a real case study. Results of artificial instances indicate that the models developed can be used to obtain close to optimal solutions within an acceptable computing time. Results of the case study can facilitate the decision-makers to develop the waste clean-up with minimised total cost and clean-up time by selecting the right location of TDWMSs and setting up the proper waste clean-up schedule.
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ISSN:0956-053X
1879-2456
1879-2456
DOI:10.1016/j.wasman.2020.09.023