Optimal assortment planning under capacity constraint : single and multi-firm systems using transshipments
Date
Authors
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Print ISSN
Electronic ISSN
Publisher
Volume
Issue
Pages
Language
Type
Journal Title
Journal ISSN
Volume Title
Attention Stats
Usage Stats
views
downloads
Series
Abstract
To survive in today's competitive market, firms need to meet customer expectations by offering high quality products with high variety. However, there might be some physical and financial constraints limiting the assortment size. The process of finding the optimal product assortment by considering both the benefits of a large assortment as well as the costs and limits of it is known as assortment planning. In this thesis, assortment planning is analyzed under predetermined assortment capacity limits for two cases. First, a single firm's optimal assortment problem is studied to maximize its profits. Second, assortment planning problem of a system of multiple firms is investigated jointly, where firms are interacting through product sharing, called transshipments. Transshipments are known to increase product availability, thus decreasing stock-outs. Transshipments have been always utilized as an emergency demand satisfaction action in support of inventory management in the literature. Differently, in this study, transshipments are evaluated in advance of inventory management while making the assortment planning of firms. In both problems, demand is defined to have an exogenous model, where each customer has a predetermined preference for each product from the potential set. Proportional demand substitutions are also allowed from an out of assortment product to others. The results on the optimal assortment of a single firm are used as a benchmark to the optimal assortments of multiple firms communicating through transshipments. By relying on proven optimality results, it is shown how easily optimal assortments can be obtained compared to a full enumeration. Extensive numerical analyses are reported on the performances of the heuristic algorithm and sensitivity of optimal assortments to system parameters.