Hybrid genetic search for the traveling salesman problem with hybrid electric vehicle and time windows

Abstract

This article proposes a hybrid genetic search for the traveling salesman problem considering a hybrid electric vehicle and time windows. The developed approach includes a specific operator based on the order crossover (OX) to obtain improved solutions, as well as a search limitation strategy and an efficient move evaluation scheme to speed up the local search phase. Extensive computational experiments were conducted on more than 200 benchmark instances, and the proposed algorithm revealed to be effective in systematically finding high-quality solutions when compared to those achieved by the best heuristic for the problem. A number of improved solutions were found, especially for the larger and more challenging cases, for which our algorithm performed, on average, 9 times faster than the quickest method available. Moreover, we also examine the frequency distribution of the battery operation mode usage associated with the best solutions found.