A hybrid algorithm for the multi-depot vehicle scheduling problem arising in public transportation

• Published in: International journal of industrial engineering computations Vol. 10; no. 3; pp. 361 - 374
• Main Authors: Marín Moreno, César Augusto, Escobar Falcón, Luis Miguel, Bolaños, Rubén Iván, Subramanian, Anand, Escobar Zuluaga, Antonio Hernando, Granada Echeverri, Mauricio
• Format: Journal Article
• Language: English
• Published: Growing Science 01.07.2019
• Subjects: Bus Rapid Transit; Matheuristics; Set Partitioning; Tactical Planning; Vehicle Scheduling
• ISSN: 1923-2926; 1923-2934
• DOI: 10.5267/j.ijiec.2019.2.002

In this article, a hybrid algorithm is proposed to solve the Vehicle Scheduling Problem with Multiple Depots. The proposed methodology uses a genetic algorithm, initialized with three specialized constructive procedures. The solution generated by this first approach is then refined by means of a Set Partitioning (SP) model, whose variables (columns) correspond to the current itineraries of the final population. The SP approach possibly improves the incumbent solution which is then provided as an initial point to a well-known MDVSP model. Both the SP and MDVSP models are solved with the help of a mixed integer programming (MIP) solver. The algorithm is tested in benchmark instances consisting of 2, 3 and 5 depots, and a service load ranging from 100 to 500. The results obtained showed that the proposed algorithm was capable of finding the optimal solution in most cases when considering a time limit of 500 seconds. The methodology is also applied to solve a real-life instance that arises in the transportation system in Colombia (2 depots and 719 services), resulting in a decrease of the required fleet size and a balanced allocation of services, thus reducing deadhead trips.