1 A Fuzzy - Control - Based Quick Response Reorder Scheme for Retailing of Seasonal Apparel

A fuzzy-control-based Quick Response (QR) reorder scheme for seasonal apparel is being developed. The fuzzy-control scheme uses Mamdani inference logic. A stochastic computer simulation model of the apparel-retailing process is employed to evaluate the performance of the proposed scheme vis-a-vis that of existing approaches. Background “Quick Response” (QR) for apparel retailing refers to the application of well-defined quality-management and industrial engineering practices, together with the use of available hard and soft technologies, to reduce significantly the length of the apparel pipeline and thus opening the door to a different supply procedure. Research has shown that the successful implementation of QR for apparel retail involves: a collapsed and responsive supply system; smaller initial store inventories of garments; Point-of-Sale (POS) tracking; bar-coding of merchandise and Electronic Data Interchange (EDI); continual reestimation of a season's customer demand; and frequent reorders on the vendor that allow matching of the stock-keeping-unit (SKU) assortment being offered to what the customer wants. Nuttle et al. (1991) developed a stochastic simulation model of the apparel-retailing process for a retail store selling seasonal apparel, i.e., merchandise with a shelf life of 4-6 months. The model was designed to explore the applicability and benefits of QR vis-a-vis traditional retailing procedures and, in particular, to aid in the development of demand re-estimation and reorder algorithms capable of adjusting the SKU mix on the shelves to reflect true, as opposed to buyer forecast, consumer desires. The model has been used to quantify the retail performance characteristics (service and economic) of QR and more traditional procedures for seasonal apparel to investigate of the underlying performance differences between the two operating paradigms, as well as to explore the limitations on QR effectiveness imposed by season length and the number of items offered per SKU. In this paper we develop a fuzzy-controlbased alternative to the QR reorder schemes that have been examined in the previous studies. Simulation Model of QR Retailing Process for Seasonal Apparel Retail SKU Inventory Reorders Initial Supply