Spatiotemporal Multi-objective Optimization for Competitive Mobile Vendors' Location and Routing Using De Facto Population Demands

Mobile vendors such as food trucks have become viable players in the food service market as a relatively new business model based on high mobility and flexibility. To remain competitive against typical brick and mortar establishments, it is important for mobile food vendors to operate at sites that will generate sufficient revenue, which may mean navigating to locations of high demand and low competition. This study addresses the optimal locations and routing of mobile vendors along different objectives that could contribute to higher revenue. We develop a multi-objective spatiotemporal optimization of food trucks by explicitly considering the dynamics of urban population distribution and thus potential customer demand. For an empirical application, we focus on the location and routing problems of food trucks in Seoul, Korea. The results show that several noninferior solution sets are possible for simultaneously maximizing demand capture while reducing market competition. A routing between optimal locations for food trucks is also suggested. This research could provide useful insights and practical solutions that are directly applicable to various mobile vendors.