Location Optimization for a Mobile Food Vendor Using Public Data
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The aim of this thesis is to formulate and solve location optimization model for a mobile food vendor to maximize profits. The model suggests dynamic location, based on service quality decisions (cuisine, price and other service criteria) from online yelp reviews and from geographic and demographic data. A mixed integer programming model is developed based on time discretization. During a discrete time period, the food vendor can either be stationed at a location generating profit or be moving to another location (no profit). Due to the computational limits of the MIP, several heuristic strategies are developed. Results demonstrate a case study based from New York City metropolitan area.