Department: Supply Chain and Information Management

Programme: Bachelor of Business Administration (Honours) in Supply Chain Management

Project Title: A Decision Support System for Food Delivery Routing – A Food Delivery Platform Case Study

Supervisor: Dr Collin WONG

Students: HO Chun Yu Angel, HOW Shuk Ching Cathy, LO Hoi Ching Koey, MAN Sze Wing Maggie, WONG Tsz Chun Matthew


Food delivery has been gaining popularity due to the development of technology and the change of lifestyle. Since the COVID-19 broke out, avoiding being infected is essential. Thus, a series of implementations were adopted by the Hong Kong government, such as restrictions on dine-in service. This surges the demands of food delivery and urges the development of the food delivery industry. However, there are some problems in the current delivery system which lengthen the delivery time and affect the food quality. Currently, the food delivery apps use a heuristic method to distribute orders to nearby drivers, and the shortest travelling time and lower cost cannot be guaranteed. Besides, drivers decide their travelling route by themselves, which may lead to lower efficiency. We propose a two stages decision support food delivery model for minimizing the food delivery time. Stage 1 makes decisions for assigning drivers to different restaurants from their original stations. Stage 2 plans drivers’ routes to deliver customer orders based on their assigned orders. This, in turn, improves the food delivery service and provides better customer service. Three cases with different order sizes were studied to analyze the profit and completion time under different conditions. This decision support system also compares the performances of the newly proposed routing model against the traditional food delivery model. This provides restaurants owners guidelines in choosing different food delivery models under different situations. Lastly, several managerial insights were suggested for restaurants to improve their delivery services, like cost saving and reducing service time.


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