Solving a multi-period inventory routing problem with stochastic unstationary demand rates

The inventory routing problem (IRP) is one of the most challenging problems in logistics and supply chain management (SCM). It aims to optimise the integration between inventory management and vehicle routing operations in a supply network. IRP arise involving the inventory and distribution process...

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Main Author:	Muhammad Khodri Harahap, Afif Zuhri
Format:	Thesis
Language:	eng eng eng
Published:	2022
Subjects:	QA76 Computer software
Online Access:	https://etd.uum.edu.my/10221/1/permission%20to%20use-NOT%20ALLOWED.pdf https://etd.uum.edu.my/10221/2/s902153_01.pdf https://etd.uum.edu.my/10221/3/s902153_02.pdf
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id	my-uum-etd.10221
record_format	uketd_dc
spelling	my-uum-etd.102212023-01-12T01:01:23Z Solving a multi-period inventory routing problem with stochastic unstationary demand rates 2022 Muhammad Khodri Harahap, Afif Zuhri Abdul Rahim, Kamarul Irwan College of Business (COB) College of Business QA76 Computer software The inventory routing problem (IRP) is one of the most challenging problems in logistics and supply chain management (SCM). It aims to optimise the integration between inventory management and vehicle routing operations in a supply network. IRP arise involving the inventory and distribution process consisting of a set of vehicle routes, delivery quantities, and delivery times that minimise the total inventory and transportation costs with the implementation of vendor-managed inventory (VMI) policies. VMI is a policy in which a supplier assumes the responsibility of maintaining the inventory for the customer while ensuring that they will not run out of stock. Thus, this research aims to develop a mathematical model known as a mixed-integer programming model to solve a multi-period stochastic unstationary inventory routing problem (MP-SUIRP) in which the demand is considered non-consistent over time. The problem focuses on the one-to-many network, where a single warehouse needs to serve several customers over the planning horizon. The inventories are transported from a warehouse to a set of customers using a fleet of homogeneous vehicles to meet the customer's requirements. As a condition, a customer is allowed to be visited once over a given period. A customer’s demand rates in each period are stochastic unstationary and the warehouse is implementing a VMI. This problem is solved using a simulation software called a mathematical programming language (AMPL) to achieve the optimization result. The mathematical model is modified by the addition of a forecasting technique to determine the customer demand rates to supply the inventories and develop the best vehicle routes for the delivery process. A sensitivity analysis is performed on the critical parameters that influence the optimization results. The computational results show that the algorithms that implement this modified formulation can achieve a better optimization result. Thus, this study helps the organisation optimise the total inventory and transportation costs for the benefit of financial performance. 2022 Thesis https://etd.uum.edu.my/10221/ https://etd.uum.edu.my/10221/1/permission%20to%20use-NOT%20ALLOWED.pdf text eng staffonly https://etd.uum.edu.my/10221/2/s902153_01.pdf text eng staffonly https://etd.uum.edu.my/10221/3/s902153_02.pdf text eng staffonly phd doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng eng
advisor	Abdul Rahim, Kamarul Irwan
topic	QA76 Computer software
spellingShingle	QA76 Computer software Muhammad Khodri Harahap, Afif Zuhri Solving a multi-period inventory routing problem with stochastic unstationary demand rates
description	The inventory routing problem (IRP) is one of the most challenging problems in logistics and supply chain management (SCM). It aims to optimise the integration between inventory management and vehicle routing operations in a supply network. IRP arise involving the inventory and distribution process consisting of a set of vehicle routes, delivery quantities, and delivery times that minimise the total inventory and transportation costs with the implementation of vendor-managed inventory (VMI) policies. VMI is a policy in which a supplier assumes the responsibility of maintaining the inventory for the customer while ensuring that they will not run out of stock. Thus, this research aims to develop a mathematical model known as a mixed-integer programming model to solve a multi-period stochastic unstationary inventory routing problem (MP-SUIRP) in which the demand is considered non-consistent over time. The problem focuses on the one-to-many network, where a single warehouse needs to serve several customers over the planning horizon. The inventories are transported from a warehouse to a set of customers using a fleet of homogeneous vehicles to meet the customer's requirements. As a condition, a customer is allowed to be visited once over a given period. A customer’s demand rates in each period are stochastic unstationary and the warehouse is implementing a VMI. This problem is solved using a simulation software called a mathematical programming language (AMPL) to achieve the optimization result. The mathematical model is modified by the addition of a forecasting technique to determine the customer demand rates to supply the inventories and develop the best vehicle routes for the delivery process. A sensitivity analysis is performed on the critical parameters that influence the optimization results. The computational results show that the algorithms that implement this modified formulation can achieve a better optimization result. Thus, this study helps the organisation optimise the total inventory and transportation costs for the benefit of financial performance.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Muhammad Khodri Harahap, Afif Zuhri
author_facet	Muhammad Khodri Harahap, Afif Zuhri
author_sort	Muhammad Khodri Harahap, Afif Zuhri
title	Solving a multi-period inventory routing problem with stochastic unstationary demand rates
title_short	Solving a multi-period inventory routing problem with stochastic unstationary demand rates
title_full	Solving a multi-period inventory routing problem with stochastic unstationary demand rates
title_fullStr	Solving a multi-period inventory routing problem with stochastic unstationary demand rates
title_full_unstemmed	Solving a multi-period inventory routing problem with stochastic unstationary demand rates
title_sort	solving a multi-period inventory routing problem with stochastic unstationary demand rates
granting_institution	Universiti Utara Malaysia
granting_department	College of Business (COB)
publishDate	2022
url	https://etd.uum.edu.my/10221/1/permission%20to%20use-NOT%20ALLOWED.pdf https://etd.uum.edu.my/10221/2/s902153_01.pdf https://etd.uum.edu.my/10221/3/s902153_02.pdf
_version_	1776103768565219328

Solving a multi-period inventory routing problem with stochastic unstationary demand rates

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