FIT5160 Business Process Modelling, Design and Simulation
Semester 2, 2020
Assignment 2 Scenario – Business Processes Evaluation @ LSS1
A supermarket chain plans to open a store in your local residential area, named Local Supermarket Store (LSS). You are hired by LSS to help them plan the business operations of the new store. While the LSS executives believe they have collected sufficient empirical data of the various factors surrounding LSS, they want you to build a number of simulation models so that they can better understand the customer flows and queuing processes in LSS.
The pilot project at hand involves only two simulation models and focuses on an off-peak setting where at most two checkouts are open. The off-peak setting is valid for four hours, so it is reasonable to run the simulation for 240 minutes. Furthermore, to facilitate an easier first-cut comparison between the two models, a fixed random seed set at 2 is recommended. Because LSS plans to use these different models later, it is important that each model sheet has a limit of one model.
Empirical investigation has indicated that it is reasonable to model the total customer arrival process to the store as a Poisson process with a mean of three customers per minute. As for the queue configuration, LSS feels that each checkout counter should have its own queue – that is, when a customer arrives to the checkout point, s/he will choose which queue (if there is any) to join; and the customer is not allowed to switch queues after making the initial choice. LSS executives think one line for each checkout is better for psychological reasons; as one long line might deter customers from entering the store.
Empirical investigation has also shown that there are basically two types of customers, and they need to be considered separately:
• Type 1 are the light shoppers who buy only a few items (normally fewer than 15 items). It is estimated that about 65 percent of the customers arriving to the store are light shoppers. Their shopping time (i.e. the time customers spend in the store walking around and picking up their groceries) follows a triangular distribution with a most likely value of 6 minutes, a minimum value of 2 minutes, and a maximum value of 10 minutes.
• Type 2 are the heavy shoppers who buy several items (normally more than 15 items). They represent about 35 percent of the arriving customers. Their shopping time is also triangularly distributed with a most likely value of 15 minutes, a minimum value of 10 minutes, and a maximum value of 20 minutes.
1 Disclaimer: The content of this scenario is fictitious.
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FIT5160 BPM, D&S Semester 2, 2020 Assignment 2 Scenario
In the first simulation model, the two checkout stations are identical where their service time is normally distributed with a mean of 30 seconds and a standard deviation of 10 seconds. After shopping, the customers will choose the shortest line to join. After the customers have paid for their goods, they immediately leave the store.
In the second simulation model, to improve the service for the light shoppers, LSS is thinking about dedicating one of the checkout counters (Checkout 1) to this customer group. In other words, only light shoppers are allowed to use Checkout 1. The other checkout (Checkout 2) will handle both heavy and light shoppers. However, empirical interviews indicate that light shopper will not choose the regular lane unless there are at least two more shoppers are waiting in line at the express lane compared to the regular lane. The service times for the express checkout (i.e. Checkout 1) are exponentially distributed with a mean of 15 seconds, whereas the service times for the regular checkout (i.e. Checkout 2) are exponentially distributed with a mean of 42 seconds.
For each model, LSS wants to keep track of (i.e., plots) the average cycle time, queue length, and waiting time in the queue. To understand the variability, they also want to see the standard deviation of these three metrics. They would like to track the maximum waiting time and the maximum number of customers in line. In addition, to better understand the system dynamics, plots of the actual queue lengths over time are required features of the model. Furthermore, the time customers spent shopping (average and standard deviation), the number of customers in the store (average and standard deviation), and the separate cycle times for heavy and light shoppers (average and standard deviation) are all required statistics the LSS executives would like to see.
Dr Caddie Gao 25 September 2020
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