The University of Southampton
University of Southampton Institutional Repository

Joint pricing and inventory decisions for substitutable perishable products under demand uncertainty

Joint pricing and inventory decisions for substitutable perishable products under demand uncertainty
Joint pricing and inventory decisions for substitutable perishable products under demand uncertainty
The focus of the work of this thesis is to develop demand uncertainty models for retailers making optimal pricing and inventory decisions on substitutable and perishable products. In particular we study three applications of demand uncertainty models: (i) a stochastic programming approach for two substitutable and perishable products over a two period planning horizon; (ii) a stochastic programming approach for multiple substitutable and perishable products over multiple periods; (iii) a robust optimization approach for two substitutable and perishable products over a single period. The three models support decision makers in retailing to incorporate the future demand uncertainty and substitution between similar products into their pricing and inventory decisions. In the context of a stochastic programming approach for two substitutable and perishable products problem over two periods, a stochastic dynamic programming model has been proposed in which the retailer aims at maximizing the total profit. The property of decision variables is analysed, an efficient search algorithm is developed to obtain the optimal results. Numerical results are reported using a case study based on a high-street fashion company. The sensitivity of the models' parameters is also analysed to address the great importance of data accuracy on decision variables and total profit. The benefits of considering pricing and inventory decisions simultaneously will be demonstrated and the total profit is observed to be significantly improved through the consideration of price substitution between substitutable products. In the context of a stochastic programming approach for multiple substitutable and perishable products problem over multiple periods, two stochastic dynamic programming models are proposed in which the decision maker can employ multiple markdowns on the prices. An efficient search algorithm has been developed by analysing the property of the decision variables. The benefits of making joint pricing and inventory decisions, considering substitutions between similar products; and dividing selling periods into more periods have been quantified.
In the context of the robust optimization approach, we relax the assumption on the complete knowledge of the demand distribution from the stochastic dynamic programming model and develop a robust optimization model. The demand function is assumed to belong to an uncertainty set, and our objective is to find the optimal ordering quantity and price which maximize the worst-case profit. We extend a Newsvendor model in the face of uncertainty to consider the optimal pricing and inventory decisions of a retailer. Numerical tests are presented based on a case study of the retailing branch of a solar panel manufacturer. The trade-off between uncertainty level and total profits is illustrated, the sensitivity of parameters is also analysed
University of Southampton
Fang, Fei
0be9695c-e812-4001-86e3-3ec3b553a3aa
Fang, Fei
0be9695c-e812-4001-86e3-3ec3b553a3aa
Nguyen, Tri-Dung
a6aa7081-6bf7-488a-b72f-510328958a8e

Fang, Fei (2016) Joint pricing and inventory decisions for substitutable perishable products under demand uncertainty. University of Southampton, Southampton Business School, Doctoral Thesis, 166pp.

Record type: Thesis (Doctoral)

Abstract

The focus of the work of this thesis is to develop demand uncertainty models for retailers making optimal pricing and inventory decisions on substitutable and perishable products. In particular we study three applications of demand uncertainty models: (i) a stochastic programming approach for two substitutable and perishable products over a two period planning horizon; (ii) a stochastic programming approach for multiple substitutable and perishable products over multiple periods; (iii) a robust optimization approach for two substitutable and perishable products over a single period. The three models support decision makers in retailing to incorporate the future demand uncertainty and substitution between similar products into their pricing and inventory decisions. In the context of a stochastic programming approach for two substitutable and perishable products problem over two periods, a stochastic dynamic programming model has been proposed in which the retailer aims at maximizing the total profit. The property of decision variables is analysed, an efficient search algorithm is developed to obtain the optimal results. Numerical results are reported using a case study based on a high-street fashion company. The sensitivity of the models' parameters is also analysed to address the great importance of data accuracy on decision variables and total profit. The benefits of considering pricing and inventory decisions simultaneously will be demonstrated and the total profit is observed to be significantly improved through the consideration of price substitution between substitutable products. In the context of a stochastic programming approach for multiple substitutable and perishable products problem over multiple periods, two stochastic dynamic programming models are proposed in which the decision maker can employ multiple markdowns on the prices. An efficient search algorithm has been developed by analysing the property of the decision variables. The benefits of making joint pricing and inventory decisions, considering substitutions between similar products; and dividing selling periods into more periods have been quantified.
In the context of the robust optimization approach, we relax the assumption on the complete knowledge of the demand distribution from the stochastic dynamic programming model and develop a robust optimization model. The demand function is assumed to belong to an uncertainty set, and our objective is to find the optimal ordering quantity and price which maximize the worst-case profit. We extend a Newsvendor model in the face of uncertainty to consider the optimal pricing and inventory decisions of a retailer. Numerical tests are presented based on a case study of the retailing branch of a solar panel manufacturer. The trade-off between uncertainty level and total profits is illustrated, the sensitivity of parameters is also analysed

Text
Final PhD thesis - Fei Fang.pdf - Version of Record
Available under License University of Southampton Thesis Licence.
Download (2MB)

More information

Published date: July 2016
Organisations: University of Southampton, Southampton Business School

Identifiers

Local EPrints ID: 399814
URI: http://eprints.soton.ac.uk/id/eprint/399814
PURE UUID: e28bba51-767b-4e05-87a6-72ede8829384
ORCID for Tri-Dung Nguyen: ORCID iD orcid.org/0000-0002-4158-9099

Catalogue record

Date deposited: 18 Feb 2017 00:23
Last modified: 31 Jul 2019 00:37

Export record

Contributors

Author: Fei Fang
Thesis advisor: Tri-Dung Nguyen ORCID iD

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×