Integrating Hungarian and A* search for indoor navigation of hypermarkets

The proliferation of giant hypermarkets propelled the demand of indoor positioning and navigation system for better customers' shopping experience. A customer that moves around a massive shopping area, for example 500,000-square-foot needs route guidance to search for the desired items and its location. The retailer on other hand wants to send real-time messages based on the customer's current location in the market. This paper addresses aforementioned problem and presents an intelligent solution for route problem for customer. Raw floor map of supermarket under consideration has been manually transformed into graph for combinatorial optimization. To meet the desired objective, Hungarian's and A∗ Search algorithms have been used in a cascaded manner to facilitate customer in two ways: (1) Chronological sequencing of items list will be suggested to customer based on the distance between current customer location and the location of item of his interest (2) Customer can also view the suggested single shortest path connecting every location of item of his shopping list based on A∗ findings. Once the proposed intelligent system navigation service is deployed on customer's smartphone, he or she can send or share item list with system to receive traces of desired location within premises. Results show that Hungarian Algorithm will assign optimal ordering for items to be purchased. Similarly A∗ search results in minimal iterations showing less time consumption and less number of nodes showing least memory requirement compared to Breadth first whilst searching for shortest route.