Abstract
One of the biggest challenges that the current manufacturers and retailers are facing is to manage huge varieties of short lifecycle items to meet various consumer preferences. This study proposes an inventory management policy with a demand forecasting algorithm. In this algorithm, the discrete probability distribution is assumed and the parameters to define the distribution are estimated dynamically so that it adapts demand pattern changes during the sales season. The proposal is evaluated with the sales data disclosed by a real company and shows that the policy successfully increases the expected profit of the company.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Logistics Systems and Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.