A hybrid method for optimizing shopping lists oriented to retail store costumers

Abstract

In the present day, one of the most common activities of everyday life is going to a supermarket or similar retail spaces to buy groceries. Many consumers organizations like The European Consumer Organization [1], advise buyers to prepare a “grocery list” in order to be ready for this activity. The present work proposes a system that helps to develop this activity in several ways: Firstly, it enables the user to create lists with different levels of abstraction: from concrete products to generic ones (or families of products). Secondly, the lists are collaborative and can be shared with other users. Finally, it automatically determines the best store to buy a given product using the proposed optimization algorithm. Furthermore, the optimization algorithm assigns a part of the list to each user balancing the cost that every user has to pay and choosing the cheapest supermarket where they have to buy.