Evolutionary Algorithms for the Traveling Salesman with Multiple Passengers and High Occupancy Problem

As a generalization of the Travelling Salesman Problem, the Travelling Salesman with Multiple Passengers and High Occupancy Problem considers real-world aspects with environmental implications. This paper presents a set of features concerning the study of this new optimization problem, including a mixed-integer programming model and its linearization, a group of artificial instances, and four heuristics based on the Genetic, Memetic, and Transgenetic metaheuristics. The instances are submitted to Gurobi solver to establish a benchmark. Heuristics' parameters are tuned using the Irace tool and later compared through a computational experiment. A statistical analysis based on Friedman tests pointed to a superior performance of TGALS.