Abstract
This work aims at improving the quality of the service provided to the customers within real-life and customized demand-responsive transportation systems. Therefore, a new bi-objective model is designed to minimize both the total transit time which induces lower costs for the transportation service providers and the total waiting time for the travellers. To solve the new problem, an evolutionary algorithm is proposed based on two perturbation operators. A comparison between the proposed method and a hybrid evolutionary one from the literature is carried out. Preliminary computational experiments show the effectiveness of our method regardless of the complexity of the evolutionary schema operated. Some promising outputs are obtained allowing us to follow up the research for larger-scale transport-on-demand problems.
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References
Aggoune-Mtalaa, W., Aggoune, R.: An optimization algorithm to schedule care for the elderly at home. Int. J. Inf. Sci. Intell. Syst. 3(3), 41–50 (2014)
Amroun, K., Habbas, Z., Aggoune-Mtalaa, W.: A compressed generalized hypertree decomposition-based solving technique for non-binary constraint satisfaction problems. AI Commun. 29(2), 371–392 (2016)
Bennekrouf, M., Aggoune-Mtalaa, W., Sari, Z.: A generic model for network design including remanufacturing activities. Supply Chain Forum 14(2), 4–17 (2013)
Braekers, K., Caris, A., Janssens, G.K.: Exact and meta-heuristic approach for a general heterogeneous dial-a-ride problem with multiple depots. Transp. Res. Part B Methodol. 67, 166–186 (2014)
Chassaing: Instances of chassaing (2020). http://fc.isima.fr/~lacomme/Maxime/. Accessed 19 July 2020
Chassaing, M., Duhamel, C., Lacomme, P.: An ELS-based approach with dynamic probabilities management in local search for the dial-a-ride problem. Eng. Appl. Artif. Intell. 48, 119–133 (2016)
Cordeau, J.F., Laporte, G.: A tabu search heuristic for the static multi-vehicle dial-a-ride problem. Transp. Res. Part B Methodol. 37(6), 579–594 (2003)
Djenouri, Y., Habbas, Z., Aggoune-Mtalaa, W.: Bees swarm optimization metaheuristic guided by decomposition for solving max-sat. In: ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence, vol. 2, pp. 472–479 (2016)
Masmoudi, M.A., Braekers, K., Masmoudi, M., Dammak, A.: A hybrid genetic algorithm for the heterogeneous dial-a-ride problem. Comput. Oper. Res. 81, 1–13 (2017)
Molenbruch, Y., Braekers, K., Caris, A.: Operational effects of service level variations for the dial-a-ride problem. CEJOR 25(1), 71–90 (2015). https://doi.org/10.1007/s10100-015-0422-7
Nasri, S., Bouziri, H.: Improving total transit time in dial-a-ride problem with customers-dependent criteria. In: 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), pp. 1141–1148 (2017)
Nasri, S., Bouziri, H., Aggoune-Mtalaa, W.: Customer-oriented dial-a-ride problems: a survey on relevant variants, solution approaches and applications. In: Ben Ahmed, M., Mellouli, S., Braganca, L., Anouar Abdelhakim, B., Bernadetta, K.A. (eds.) Emerging Trends in ICT for Sustainable Development. ASTI, pp. 111–119. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-53440-0_13
Nasri, S., Bouziri, H., Aggoune-Mtalaa, W.: Dynamic on demand responsive transport with time-dependent customer load. In: Ben Ahmed, M., et al. (eds.) SCA 2020. LNNS, vol. 183, pp. 395–409. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-66840-2_30
Paquette, J., Bellavance, F., Cordeau, J.F., Laporte, G.: Measuring quality of service in dial-a-ride operations: the case of a Canadian city. Transportation 39(3), 539–564 (2012)
Parragh, S.N.: Introducing heterogeneous users and vehicles into models and algorithms for the dial-a-ride problem. Transp. Res. Part C Emerging Technol. 19(5), 912–930 (2011)
Rezgui, D., Bouziri, H., Aggoune-Mtalaa, W., Siala, J.C.: An evolutionary variable neighborhood descent for addressing an electric VRP variant. In: Sifaleras, A., Salhi, S., Brimberg, J. (eds.) ICVNS 2018. LNCS, vol. 11328, pp. 216–231. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-15843-9_17
Rezgui, D., Bouziri, H., Aggoune-Mtalaa, W., Siala, J.C.: A hybrid evolutionary algorithm for smart freight delivery with electric modular vehicles. In: 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA), pp. 1–8. IEEE (2018)
Rezgui, D., Siala, J.C., Aggoune-Mtalaa, W., Bouziri, H.: Towards smart urban freight distribution using fleets of modular electric vehicles. In: Ben Ahmed, M., Boudhir, A.A. (eds.) SCAMS 2017. LNNS, vol. 37, pp. 602–612. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-74500-8_55
Zhang, Z., Liu, M., Lim, A.: A memetic algorithm for the patient transportation problem. Omega 54, 60–71 (2015)
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Nasri, S., Bouziri, H., Aggoune-Mtalaa, W. (2023). A Bi-objective Evolutionary Algorithm to Improve the Service Quality for On-Demand Mobility. In: Ben Ahmed, M., Abdelhakim, B.A., Ane, B.K., Rosiyadi, D. (eds) Emerging Trends in Intelligent Systems & Network Security. NISS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 147. Springer, Cham. https://doi.org/10.1007/978-3-031-15191-0_1
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