A Mcdonald's case study by using multi-objective optimization
In today’s world, queue is a common situation in our life. Whenever we go to the bank or fast food restaurant, we are bound to wait in line to get our transactions done or to buy food. Hence, the study of queue is definitely an important element of certain businesses and organizations in order to...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/45048 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In today’s world, queue is a common situation in our life. Whenever we go to the bank or
fast food restaurant, we are bound to wait in line to get our transactions done or to buy
food. Hence, the study of queue is definitely an important element of certain businesses
and organizations in order to serve their customers better. This is also where optimization
techniques play an important role to optimize elements such as cost and waiting time in
queue. The combination of the study of queue and optimization can generate results
which are able to translate directly to a better customer service while maintaining
profitability for an organization.
In this project, the author will introduce the concept and elements in queuing system and
multi-objective optimization. Then, a case study on Nanyang Technological University
(NTU) McDonald’s Branch queue is undertaken and presented. A collection of the
McDonald’s queue during a certain period of time is carried out and analysis on the
queue, which resembles the M/M/c and M/G/c is carried out and explained. A MATLAB
simulation for the M/M/c and M/G/c will also be carried out. Thereafter, an optimization
for two objectives, which are the waiting time in queues and cost of McDonald’s counters
is carried out to obtain pareto frontiers of nondominated solutions. A second optimization
for the mean waiting time in queue, cost and mean service time which is related to the
staffs’ hiring and training will also be carried out for this project. Various pareto frontiers
will be identified from this second optimization and the results of the simulation and
optimization will also be discussed in the report. |
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