Since impulse purchases depend on the products exposed to the customers, the control of customer traffic in the store is crucial. During shopping, generally the customer has certain products in his mind that he plans to buy. We refer to these products as shopping list items. In order to complete shopping, the customer has to visit the shelves on which these shopping list items are located. Consequently, the location of shopping list items plays a critical role in controlling the customer traffic in the store.
In practice, end-of-aisle locations are high customer traffic areas. To benefit this, at the end of shelf rows there are end caps to display samples of high impulse purchase
revenue or promotion items. This is another point that should be taken into account during layout design.
Other than the locations of shopping list items, the layout design model should clearly identify the walkways that the customer can use in the store. These walkways define the possible set of routes the customer may follow. By locating products with high impulse purchase revenue along the walkways the customer follows, it is possible to increase the visibility of these products, and consequently the potential impulse purchase revenue. In grid layout, the walkways are defined by the aisles between the shelf rows. Depending on the length and orientation of aisles, we may have different grid layout realizations as shown in Fig. 12.
Fig. 12. Different grid layout realizations
In order to capture these aspects of grid layout, we define a basic layout compo-nent, which we refer to as grid unit. A grid unit contains a number of parallel shelf rows and aisle clearances between these shelf rows. At the end of shelf rows, there are end caps to display products having high impulse purchase rates. In Fig. 13, a grid unit having two shelf rows is presented. The grid unit has a square shape and its dimensions are proportional to the number of shelf rows it contains. The final layout consists of a set of connected grid units and perimeter shelves along the boundaries
of the store. Because of square shape design, the grid units can be rotated resulting in different layout configurations with respect to aisle orientations. In addition, given that two neighboring grid units have the same aisle orientation, one or more of the corresponding shelf rows in these grid units can be connected resulting in longer aisles and shelf rows.
End Cap End Cap
End Cap End Cap
Walkway Clearance Right Side
Left Side
Shelf Rows
Fig. 13. A grid unit with two shelf rows
Once aisle orientations of the grid units are fixed and connected shelf row deci-sions are made, the walkways the customer can use are clearly defined in the final layout due to the aisle structure inherited in each grid unit. We consider this walk-way skeleton as a network on which the customer can use different routes to complete his shopping. Depending on the shopping route, the customer may see the products located on the shelves within the aisles he passes through. In Fig. 14, examples for shelf row connection and walkway network are presented for a sample layout.
It is possible to find the minimum number of grid units for a given net shelf space requirement in the retail facility by using a mathematical programming model. The model parameters and variables are given below and also shown in Fig. 15:
Shelves
Fig. 14. Grid unit based layout design and walkway network m Number of grids in vertical direction.
k Number of grids in horizontal direction.
L Total net shelf length required by the product groups.
a Average proportion of the unused shelf space over total net shelf length required by the product groups.
n Number of parallel shelf rows in a grid.
wg Width of a square unit that the grids are composed of (Edge length of the grid unit divided by number of shelf rows in the grid unit).
p Proportion of wg that is allocated for aisle clearance on one side of a shelf row.
e Depth of an aisle end cap.
The total area requirement of the store is estimated by equation (5.1), and it is also used as the objective function.
min m k n2wg2 + m n w2g + 2k n w2g (5.1)
m k ≥ ((1 + α)L − mnwg) 1
n(nwg − 2wgp − 2e + 2wmg) (5.2)
k, m, n ∈ Integer (5.3)
k
pwg pwg
pwg
2 1
1 2
1
2
e w
w
g
g
2
n wg
n = 2
m
Fig. 15. Grid layout parameters
Constraint (5.2) states that the total shelf space available in the store should be greater than or equal to the shelf space requirement of the store. The final con-straint (5.3) ensures that number of grid units is an integer.
When the minimum number of grid units is determined by using the above mathematical programming model, generally the resulting floor plan takes the shape of a skewed rectangle due to the effect of shelf space gain from perimeter shelves. To prevent unrealistic floor plans, a shape constraint can be used in the model. After fixing the number of grid units and the shape of the floor plan, it is possible to analyze alternative layout configurations for the retail store. The details of how to generate different layout configurations using grid units are presented in the next section.