Optimal inventory policy through dual sourcing

Matthew Davison (), Yuri Lawryshyn and Volodymyr Miklyukh
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Matthew Davison: School of Mathematical & Statistical Sciences, Western University Canada
Yuri Lawryshyn: Department of Chemical Engineering and Applied Chemistry, University of Toronto
Volodymyr Miklyukh: Department of Chemical Engineering and Applied Chemistry, University of Toronto

Computational Management Science, 2020, vol. 17, issue 2, No 8, 327-355

Abstract: Abstract Profit maximization in the retail and manufacturing industry is currently focused on offshore production to utilize the resulting low production costs. However, in the face of uncertain customer demand, it is difficult to determine an optimal order quantity which maximizes profit. We consider a risk-averse firm that utilizes dual-sourcing for perishable or seasonal goods with uncertain customer demand. Using real options theories, we provide two models aimed at determining optimal order quantities to maximize the firm’s expected profit. Furthermore, we can consider the demand to be an observable process correlated to a traded asset, which can be hedged to reduce profit uncertainty. A single offshore single local order period model provides a pseudo-analytical solution which can be easily solved to determine optimal offshore and local order quantities based on the manufacturers’ lead times, and a more realistic single offshore multiple local order period model which uses numerical methods to determine optimal order quantities. Finally, a method for matching distributions of expected demands based on managerial estimates can be applied to the two models, providing managers a tool for practical application.

Date: 2020
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DOI: 10.1007/s10287-020-00371-8

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