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Abstract
The core business of the retail industry consists of selling goods in small quantities to the
general public. Retailers are keen to do everything possible to make their systems more
efficient, whilst maximizing their profit. The customer demand in retail stores is influenced by
the availability, volume and location of the product displayed. Due to the recent competition in
the retailing industry, retailers are striving to improve their operations in order to run their
stores more efficiently. Managing these operations individually will obviously result in sub-
optimal overall retail store’s profit. Therefore, a decision-making process is proposed to
integrate these operations to reach a global optimal profitability instead of optimizing the two
problems individually which may result in a less profitable solution.
Currently, most retailers pursue a response-based logistics strategy and replenish their shelves
from the backroom. The shelves in the showroom are manually inspected and the remaining
stock in the backroom is estimated based on point of sales (POS) data. One key investment
retailers are likely to make is in areas that will help improve visibility of products in the supply
chain and allow real-time, accurate information to be easily accessed and shared
collaboratively with all parties within the chain. Moreover, leading retailers introduce radio
frequency identification (RFID) into their supply chains at case and pallet level for automatic
product identification and tracking. RFID readers positioned at the door between the backroom
and the showroom could automatically capture the movement of goods and update the
backroom and sales floor inventory accordingly.
The retail stores sell multiple items and have limited spaces in the backroom and display areas.
The ordering quantities and the allocated shelf space in each display area are critical retailing
operations having major impact on the financial performance of retail stores. Moreover the
store’s inventory management system carries an overall storage that combines the backroom
and showroom together. The traditional inventory management system fails to separate
between the two inventories. where, items can run out-of stock on the shelf and still be found
in the backroom or misplaced in the showroom due to lack of product traceability.
A non-linear integer programming (NLIP) model is developed to determine the inventory
replenishment and shelf space allocation decisions that jointly maximize the retailer’s profit
under shelf space and backroom storage constraints. The demand function for each item
incorporates the main effects of shelf space as well as the location effects. The products’
ordering quantities and the allocated shelf space in each display area are considered decision
variables to be determined by the proposed integrated model. In the model formulation, the
inventory investment costs are included, which are proportional to the average inventory costs,
storage costs, and display costs as components of the inventory costs. Additionally, the effect
of the display area location on the item demand is also considered. On the other hand a clear
distinction between showroom and backroom inventories through real-time inventory
monitoring using RFID is being evaluated.
The proposed model was solved using LINGO~ optimization package that uses an exact
algorithm to solve different instances of the problem till optimality. The verification and
validation of the model was done using test models and hypothetical data.
Finally, the NLIP model was implemented in a real world case study in a large retail industry
in Alexandria, Egypt providing most of the needs of a large variety of products.