Agent Based Modeling to Optimize Supermarkets Spatial Dimensions
The British University in Dubai (BUiD)
The purpose of our research is to study the impact of supermarket size and spatial dimensions on crowding. To improve supermarkets layout from the social aspect, to increase the human comfort and reduce crowding. Despite the supermarket is a major part of our life, but there is one undesirable situation that a lot of people suffer from it, which is crowding. It is the situation where the shoppers feel that the supermarket is overloaded with people at certain times. We solved this problem by providing an optimal area range for the supermarket where we reduced the crowding levels dramatically, while avoiding unnecessary increase in space dimensions. We used a simulation methodology, using Massmotion software to create and analyse the proposed scenarios. Two sets of scenarios were tested, one with 1000 shoppers per day and the other with 2000 shoppers per day. It was shown that the area range from 1450 to 1650 square meters is the optimal area of the supermarket. The results shown that an increase in the critical zones, i.e. the fresh produce, pre-prepared zone and the sixth isle of general items, had the major cause in the reduction of congestion cost, journey cost, higher LOS, such as LOS E and F. We learnt how to find the optimal area of the supermarket or any other space with minimal effect on human comfort. Our research finding shows that the uncrowded isles can be 1.3 meters width, but the crowded isles, such as the fresh produce, pre-prepared food area and the sixth isle in the general items, should be larger with minimum 2.7 times the uncrowded zones, i.e. they should have a width of 3.6 meters, as shown in the seventh scenario.
agent based modeling, supermarkets, spatial dimensions, human comfort