A recourse goal programming approach for airport bus routing problem
- 279 Downloads
In this paper, we address the airport bus routing problem (ABRP) described as follows: A company owns several buses located at the airport to transport customers from many hotels and meeting points back to the airport according to their departure times. The ABRP can be viewed as a stochastic vehicle routing problem as the presence of customers at meeting points is random. The aim is to construct a minimum cost set of vehicle routes that satisfies all customers’ timing requests and to minimize the customer’s traveling time and the airport waiting time. We propose a multi-objective stochastic program (MSP) to model the ABRP. We solve the MSP problem using a goal programming approach and a recourse approach where the recourse decision is to send a special vehicle to customers not served by bus tours. The proposed model is tested using a real life experimental data from a transportation company located in the Tunis–Carthage airport.
KeywordsMulti-objective stochastic vehicle routing problem Multi-objective stochastic programming Taxi planning Airport routing problems
- Bianchi, L., Birattari, M., Chiarandini, M., Manfrin, M., Mastrolilli, M., Paquete, L., Rossi-Doria, O., & Schiavinotto, T. (2004). Metaheuristics for the vehicle routing problem with stochastic demands. In X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo Guervos, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, & H.-P. Schwefel (Eds.), Proceedings of the 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), vol 3242 of Lecture Notes in Computer Science, (pp. 450–460). Berlin: Springer.Google Scholar
- Murata, T., & Itai, R. (2007). Local search in two-fold EMO algorithm to enhance solution similarity for multi-objective vehicle routing problems. In: S. Obayashi, K. Deb, C. Poloni, T. Hiroyasu and T. Murata (Eds.), EMO 2007 Vol. 4403, (pp. 201–215). Springer-Verlag.Google Scholar
- Shen, Z., Ordónez, F., & Dessouky, M. M. (2009). The stochastic vehicle routing problem for minimum unmet demand. chap. IV. Springer Optimization and Its Applications (pp. 349–371). Boston, MA: Springer.Google Scholar
- Zhao, Y., Li, C., Zhang, J. L., Ren, X., & Ren, W. (2012). Research on vehicle routing problem with stochastic demand based on multi-objective method. In D.S. Huang, Y. Gan, V. Bevilacqua & J. C. Figueroa (Eds.), Advanced Intelligent Computing, Lecture Notes in Computer Science, vol. 6838, (pp. 153–161). Springer: Berlin.Google Scholar