A Multi-objective approach for the vacation planning problem: a case study applied to the Department of Santander

Abstract

Tourism is a rapidly growing global sector that drives economic development and income generation worldwide. However, governments—particularly in emerging economies—face persistent challenges in infrastructure, connectivity, environmental conservation, and sustainable community development. At the same time, tourism operators struggle to access accurate destination data, while tourists encounter difficulties in designing personalized itineraries due to individual and contextual constraints. This article presents a multi-objective mixed-integer linear programming (MILP) model and a Tabu Search metaheuristic to address the vacation planning problem by incorporating both quantitative and qualitative tourist information. The MILP model efficiently solves trips of up to 2 days, while the metaheuristic effectively manages longer itineraries. Both approaches were validated using small instances with 2-day itineraries, and the metaheuristic was further assessed in extended scenarios involving 4-, 6-, and 8-day trips, considering diverse tourist profiles within the Department of Santander in Colombia’s tourism offerings.