Solving the Open-Path Asymmetric Green Traveling Salesman Problem in a Realistic Urban Environment

Abstract

In this paper, a driving route planning system for multi-point routes is designed and developed. The routing problem has modeled as an Open-Path and Asymmetric Green Traveling Salesman Problem (OAG-TSP). The main objective of the proposed OAG-TSP is to find a route between a fixed origin and destination, visiting a group of intermediate points exactly once, minimizing the $CO_2$ emitted by the car and the total distance traveled. Thus, the developed transportation problem is a complex and multi-attribute variant of the well-known TSP. For its efficient solving, three classic meta-heuristics have been used: Simulated Annealing, Tabu Search and Variable Neighborhood Search. These approaches have been chosen for its easy adaptation and rapid execution times, something appreciated in this kind of real-world systems. The system developed has been built in a realistic simulation environment, using the open source framework Open Trip Planner. Additionally, three heterogeneous scenarios have been studied in three different cities of the Basque Country (Spain): Bilbao, Gazteiz and Donostia. Obtained results conclude that the most promising technique for solving this problem is the Simulated Annealing. The statistical significance of these findings is confirmed by the results of a Friedman’s non-parametric test.