Hybrid genetic algorithm for inventory routing problem with carbon emission consideration

Inventory Routing Problem (IRP) has been continuously developed and improved due to pressure from global warming issue particularly related to greenhouse gases (GHGs) emission. The burning of fossil fuel for transportations such as cars, trucks, ships, trains, and planes primarily emits GHGs. Carbon...

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Main Author:	Choong, Jing Yee
Format:	Thesis
Language:	English
Published:	2018
Subjects:	QA Mathematics
Online Access:	http://eprints.utm.my/id/eprint/80935/1/ChoongJingYeeMFS2018.pdf
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spelling	my-utm-ep.809352019-07-24T00:10:57Z Hybrid genetic algorithm for inventory routing problem with carbon emission consideration 2018-08 Choong, Jing Yee QA Mathematics Inventory Routing Problem (IRP) has been continuously developed and improved due to pressure from global warming issue particularly related to greenhouse gases (GHGs) emission. The burning of fossil fuel for transportations such as cars, trucks, ships, trains, and planes primarily emits GHGs. Carbon dioxide (CO2) from burning of fossil fuel to power transportation and industrial process is the largest contributor to global GHGs emission. Therefore, the focus of this study is on solving a multi-period inventory routing problem (MIRP) involving carbon emission consideration based on carbon cap and offset policy. Hybrid genetic algorithm (HGA) based on allocation first and routing second is used to compute a solution for the MIRP in this study. The objective of this study is to solve the proposed MIRP model with HGA then validate the effectiveness of the proposed HGA on data of different sizes. Upon validation, the proposed MIRP model and HGA is applied on real data and parameter sensitivity analysis is performed on the MIRP model. The HGA is found to be able to solve small size and large size instances effectively by providing near optimal solution in relatively short CPU execution time. In addition, the increase in unit carbon price results in the increase of the supply chain’s total cost while the increase in carbon cap results in the decrease of supply chain’s total cost. The results from the analysis gave an indication that the unit carbon price and carbon cap need to be thoroughly designed so that it will not burden the participating companies of carbon emission regulation and environment. 2018-08 Thesis http://eprints.utm.my/id/eprint/80935/ http://eprints.utm.my/id/eprint/80935/1/ChoongJingYeeMFS2018.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:120459 masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Choong, Jing Yee Hybrid genetic algorithm for inventory routing problem with carbon emission consideration
description	Inventory Routing Problem (IRP) has been continuously developed and improved due to pressure from global warming issue particularly related to greenhouse gases (GHGs) emission. The burning of fossil fuel for transportations such as cars, trucks, ships, trains, and planes primarily emits GHGs. Carbon dioxide (CO2) from burning of fossil fuel to power transportation and industrial process is the largest contributor to global GHGs emission. Therefore, the focus of this study is on solving a multi-period inventory routing problem (MIRP) involving carbon emission consideration based on carbon cap and offset policy. Hybrid genetic algorithm (HGA) based on allocation first and routing second is used to compute a solution for the MIRP in this study. The objective of this study is to solve the proposed MIRP model with HGA then validate the effectiveness of the proposed HGA on data of different sizes. Upon validation, the proposed MIRP model and HGA is applied on real data and parameter sensitivity analysis is performed on the MIRP model. The HGA is found to be able to solve small size and large size instances effectively by providing near optimal solution in relatively short CPU execution time. In addition, the increase in unit carbon price results in the increase of the supply chain’s total cost while the increase in carbon cap results in the decrease of supply chain’s total cost. The results from the analysis gave an indication that the unit carbon price and carbon cap need to be thoroughly designed so that it will not burden the participating companies of carbon emission regulation and environment.
format	Thesis
qualification_level	Master's degree
author	Choong, Jing Yee
author_facet	Choong, Jing Yee
author_sort	Choong, Jing Yee
title	Hybrid genetic algorithm for inventory routing problem with carbon emission consideration
title_short	Hybrid genetic algorithm for inventory routing problem with carbon emission consideration
title_full	Hybrid genetic algorithm for inventory routing problem with carbon emission consideration
title_fullStr	Hybrid genetic algorithm for inventory routing problem with carbon emission consideration
title_full_unstemmed	Hybrid genetic algorithm for inventory routing problem with carbon emission consideration
title_sort	hybrid genetic algorithm for inventory routing problem with carbon emission consideration
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2018
url	http://eprints.utm.my/id/eprint/80935/1/ChoongJingYeeMFS2018.pdf
_version_	1747818283249172480

Hybrid genetic algorithm for inventory routing problem with carbon emission consideration

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