Degree Name
MS (Master of Science)
Program
Mathematical Sciences
Date of Award
8-2021
Committee Chair or Co-Chairs
Jeff Knisley
Committee Members
Michelle Joyner, Anant Godbole, JeanMarie Hendrickson
Abstract
Newsvendor problems in Operations Research predict the optimal inventory levels necessary to meet uncertain demands. This thesis examines an extended version of a single period multi-product newsvendor problem known as the ice cream vendor problem. In the ice cream vendor problem, there are two products – ice cream and hot chocolate – which may be substituted for one another if the outside temperature is no too hot or not too cold. In particular, the ice cream vendor problem is a data-driven extension of the conventional newsvendor problem which does not require the assumption of a specific demand distribution, thus allowing the demand for ice cream and hot chocolate respectively to be temperature dependent. Using Discrete Event Simulation, we first simulate a real-world scenario of an ice cream vendor problem via a demand whose expected value is a function of temperature. A sample average approximation technique is subsequently used to transform the stochastic newsvendor program into a feature-driven linear program based on the exogenous factors of probability of rainfall and temperature. The resulting problem is a multi-product newsvendor linear program with L1-regularization. The solution to this problem yields the expected cost to the ice cream vendor as well as the optimal order quantities for ice cream and hot chocolate, respectively.
Document Type
Thesis - unrestricted
Recommended Citation
Azasoo, Makafui, "Data Science and the Ice-Cream Vendor Problem" (2021). Electronic Theses and Dissertations. Paper 3957. https://dc.etsu.edu/etd/3957
Copyright
Copyright by the authors.