Route Optimization Using Genetic Algorithm for Visitors to Legends Park

Vega-Huerta H.; Rivas D.T.; Mayhuay J.H.; Chapoñan M.D.; Puelles-Bulnes M.; Gil-Calvo R.; Cabrera-Díaz J.; Elena Maquen-Niño G.L. · Revista Portuguesa de Estudos Regionais (2026) · DOI: 10.59072/rper.vi75.857

Resumen

This study presents a route optimization model based on genetic algorithms applied to Parque de las Leyendas, located in the district of San Miguel, in Lima, Peru. This space is the largest zoo in the country, with an approximate area of 130 hectares and 215 species of animals distributed in various thematic areas, which generates a complex environment for the efficient planning of routes. The proposed model simultaneously integrates three fundamental criteria: distance, time and rating of points of interest, approaching the problem from a multi-objective perspective. Unlike traditional approaches that optimize a single factor, the methodology developed allows the generation of balanced routes adapted to different visitor profiles and time constraints. The results obtained through computational simulation show improvements in the efficiency of the route and in the strategic distribution of attractions visited. In this sense, the model constitutes a tool to support the management and planning of large-scale tourist spaces, with the potential for replicability in other regional destinations that have similar territorial and operational characteristics. © (2026), (Revista Portuguesa de Estudos Regionais). All rights reserved.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional Pedro Ruiz Gallo