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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 55741 (01)
- University: Sharif University of Technology
- Department: Industrial Engineering
- Advisor(s): Khedmati, Majid
- Abstract:
- It has always been a challenge for retailers to plan which of the available goods will be displayed to the customer and at what price for each. In practice, the limited storage capacity of goods, the limited capacity of shelves, or the limited capacity of displaying goods on a web page in online stores may make it more difficult to decide on the above issues. These issues have been addressed in the literature when demand for goods is clear or a good estimate of demand can be obtained based on sales data. The purpose of this study is to investigate multi period Assortment planning, pricing and inventory planning with respect to the limited capacity of storage and display of goods in a situation where the demand for goods is not clear. More precisely, in this research, it is considered that there is a store which has a number of goods to display, but the existence of some restrictions does not allow it to display more than a certain number of goods to customers. Each product has several price options, and the store must also decide at what price each product will be displayed to the customer. The problem under consideration in this study is multi-period, and at the beginning of each period, in addition to mentioned challenges, the store must decide how many to order from each product. The capacity of the store is also limited and it can not store more than a certain number of goods in each period. The store is also unaware of the demand for goods and must design a policy for demand learning. In this dissertation, Thompson sampling method is used to learn the demand and the simultaneous problem of Assortment planning, pricing and inventory planning in each period is solved with a heuristic algorithm. To measure the performance of the proposed algorithm, the cumulative revenue obtained is compared with the revenue of a benchmark algorithm for which the demand for goods is known and it is observed that while the capacity in each period is at least equal to the demand of the period, revenue of proposed algorithm gets very close to revenue of the benchmark algorithm. Finally, the proposed algorithm was compared with one of the similar algorithms in the literature and it was observed that the revenue of the proposed algorithm, which considers the inventory limit, is very close to the revenue of the algorithm in literature, while the capacity in each period is at least equal to the demand of the period.
- Keywords:
- Assortment Planning ; Pricing ; Demand Learning ; Limited Inventory ; Freight Demand
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