Municipal solid waste allocation planning using interval programming

The provision of a reliable, feasible and sustainable municipal solid waste (MSW) management plan is essential in ensuring public health and standard of living. However, the presence of multiple parameter uncertainties within the complex network of MSW elements has been a challenge to produce reliab...

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Main Author: Li, Chengxi.
Other Authors: School of Civil and Environmental Engineering
Format: Final Year Project
Language:English
Published: 2013
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Online Access:http://hdl.handle.net/10356/52877
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-528772023-03-03T17:23:53Z Municipal solid waste allocation planning using interval programming Li, Chengxi. School of Civil and Environmental Engineering Qin Xiaosheng DRNTU::Engineering::Environmental engineering::Waste management The provision of a reliable, feasible and sustainable municipal solid waste (MSW) management plan is essential in ensuring public health and standard of living. However, the presence of multiple parameter uncertainties within the complex network of MSW elements has been a challenge to produce reliable conclusions for decision-making. An interval mixed-integer linear programming (IMILP) model was developed in this study to optimise system cost of a MSW management system. The model improved upon the existing deterministic mixed-integer linear programming (DMILP) by allowing uncertainties in the input parameters to be expressed as discrete intervals, when parameter distributions were unknown or difficult to ascertain. The integration of mixed-integer programming (MIP) allowed the model to deal with capacity expansion decisions in various management facilities. The model was applied to three policy scenarios in Foshan, China. The IMILP model illustrated a clear shift of preference from landfilling to incineration and composting, when policy goals became stricter. There was also significant uncertainty in capacities expansions that might lead to large excess capacities. The highest cost corresponded to the strictest scenario and was most sensitive to three parameters: unit transportation cost, waste generation rate and residue rate of composting. A policy scenario with moderate regulation and financial burden was recommended. It is suggested that IMILP to be integrated with chance-constrained mixed-integer linear programming (CCMILP) model in a further study of the case. This would enable planners to obtain interval solutions associated with different constraint violation risks, thereby able to evaluate system failure risk against system cost. Nonetheless, the interval solutions obtained in this study would provide planners with considerable flexibility in choosing decision alternatives that would best suit the economic, social, technological and political considerations of the city. Bachelor of Engineering (Environmental Engineering) 2013-05-29T02:04:27Z 2013-05-29T02:04:27Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52877 en Nanyang Technological University 72 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Environmental engineering::Waste management
spellingShingle DRNTU::Engineering::Environmental engineering::Waste management
Li, Chengxi.
Municipal solid waste allocation planning using interval programming
description The provision of a reliable, feasible and sustainable municipal solid waste (MSW) management plan is essential in ensuring public health and standard of living. However, the presence of multiple parameter uncertainties within the complex network of MSW elements has been a challenge to produce reliable conclusions for decision-making. An interval mixed-integer linear programming (IMILP) model was developed in this study to optimise system cost of a MSW management system. The model improved upon the existing deterministic mixed-integer linear programming (DMILP) by allowing uncertainties in the input parameters to be expressed as discrete intervals, when parameter distributions were unknown or difficult to ascertain. The integration of mixed-integer programming (MIP) allowed the model to deal with capacity expansion decisions in various management facilities. The model was applied to three policy scenarios in Foshan, China. The IMILP model illustrated a clear shift of preference from landfilling to incineration and composting, when policy goals became stricter. There was also significant uncertainty in capacities expansions that might lead to large excess capacities. The highest cost corresponded to the strictest scenario and was most sensitive to three parameters: unit transportation cost, waste generation rate and residue rate of composting. A policy scenario with moderate regulation and financial burden was recommended. It is suggested that IMILP to be integrated with chance-constrained mixed-integer linear programming (CCMILP) model in a further study of the case. This would enable planners to obtain interval solutions associated with different constraint violation risks, thereby able to evaluate system failure risk against system cost. Nonetheless, the interval solutions obtained in this study would provide planners with considerable flexibility in choosing decision alternatives that would best suit the economic, social, technological and political considerations of the city.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Li, Chengxi.
format Final Year Project
author Li, Chengxi.
author_sort Li, Chengxi.
title Municipal solid waste allocation planning using interval programming
title_short Municipal solid waste allocation planning using interval programming
title_full Municipal solid waste allocation planning using interval programming
title_fullStr Municipal solid waste allocation planning using interval programming
title_full_unstemmed Municipal solid waste allocation planning using interval programming
title_sort municipal solid waste allocation planning using interval programming
publishDate 2013
url http://hdl.handle.net/10356/52877
_version_ 1759856356956831744