Queue buildup is a problem that every fast food restaurant would like to reduce, as its effect on customer satisfaction and restaurant revenue is obviously negative. This thesis looks at how a dynamic menu management system would affect fast food restaurants, specifically how the promotion of fast products, in certain situations, would affect total revenue and queue lengths. A neural network was used to categorize products depending on their preparation time and to predict queue waiting times. A simulation approach was used to find out how the menu management system would affect the restaurant. The results are that in situations where long queues are formed, the promotion of fast products increases revenue by 7.8% and decreases queue lengths by 13.3%. In situations where little to no queues are formed, the same system still decreases queue lengths by 4.7%, but also decreases revenue by 0.2%
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-80925 |
| Date | January 2020 |
| Creators | Sawert, Adam |
| Publisher | Luleå tekniska universitet, Datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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