Data mining-based algorithm for assortment planning

作     者：Praveen Ranjan Srivastava Satyendra Sharma Simran Kaur 

作者机构：Information TechnologyIndian Institute of Management(IIM)RohatakRohtakIndia Operation and Supply ChainBirla Institute of Technology and Science(BITS)PilaniPilaniRajasthanIndia Computer ScienceBirla Institute of Technology and Science(BITS)PilaniPilaniRajasthanIndia 

出 版 物：《Journal of Management Analytics》 (管理分析学报（英文）)

年 卷 期：2020年第7卷第3期

页      面：443-457页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020205[经济学-产业经济学] 

主　　题：Retail assortment SKU rationalization data mining 

摘      要：With increasing varieties and products,management of limited shelf space becomes quite difficult for ***,an efficient product assortment,which in turn helps to plan the organization of various products across limited shelf space,is extremely important for *** can be distinguished based on quality,price,brand,and other attributes,and decision needs to be made about an assortment of the products based on these *** efficient assortment planning improves the financial performance of the retailer by increasing profits and reducing operational *** techniques can be very effective in grouping products,stores,*** help managers solve the problem of assortment *** paper proposes data mining approaches for assortment planning for profit maximization with space,and cost constraints by mapping it into well-known knapsack problem.