Winning by a Mile : A Mathematical Programming Approach to Reducing Distance and Ensuring Fairness in Travel in the FIFA World Cup

The FIFA World Cup presents a complex logistical challenge, featuring an intricate tournament schedule that requires teams to frequently move between their base camps and match venues. In this thesis, we explore the potential of mathematical programming as a tool to devise an optimal tournament schedule that reduces extensive travel and ensures fair travel distribution. We create a FIFA World Cup scheduling framework consisting of mixed integer linear programming models. The framework consists of a series of individual optimization models, crafted from the guidelines of the World Cup of 2014 and 2018. All models yield significantly improved objectives relative to the historical benchmarks of 2014 and 2018. For the models minimizing total distance traveled throughout the group stage, the results range from a decrease of 25% to 48% in distance covered compared to historical distances. For the models minimizing the distance between the least and most traveling teams among all teams, the results range from a decrease of 81% to 96% for this inner range compared to historical differences. For the models minimizing the distance between the least and most traveling teams within each group, the results range from a decrease of 83% to 98% for the sum of the groupwise inner ranges compared to the sum of the historical groupwise inner ranges. We further combine the individual objectives into a multi-objective model using the �- constraint method, thereby showcasing a Pareto front of candidate solutions that all yield results that surpass the historical benchmarks for both objectives simultaneously. Our findings strongly indicate that utilizing mathematical programming for the World Cup match scheduling process offers the potential to reduce the overall distances traveled while concurrently ensuring a more balanced distribution of travel burdens among the participants. We highlight the 2026 World Cup as an ideal prospect for implementing this approach.nhhma