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Generating Duplex Routes for Robust Bus Transport Network by Improved Multi-objective Evolutionary Algorithm Based on Decomposition

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Applications of Evolutionary Computation (EvoApplications 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12694))

Abstract

This paper proposes the duplex route generation method to evolve the bus route network which is robust to environmental changes and aims at investigating its effectiveness through the experiments. In this study, the “duplex route” corresponds to the alternative route and it has the advantage of not requiring to modify the route network in the environmental changes. To generate the duplex routes, this study employs MOEA/D as the base optimization method and introduces the following two operations in MOEA/D to increase the duplex routes while improving the fitness: (1) the crossover operation to generate the duplex routes, which is improved from the crossover operation in SEAMO2 [9] that evolves unique routes, and (2) the priority solution update operation in the enhanced MOEA/D [4] to maintain a diversity of the routes which contributes to improving the fitness. The experiments on Mandl’s benchmark problem has revealed: (1) the proposed crossover operation can generate many duplex networks as compared to the original crossover operation; (2) the priority solution update operation improves the fitness, i.e., a minimization of the passenger transportation time and the number of buses; and (3) integration of the two operations improves both the number of duplex routes and fitness, which is hard to be achieved by either operation.

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References

  1. Baaj Hadi, M., Mahmassani, H.S.: TRUST: a LISP program for the analysis of transit route configurations. Transp. Res. Rec. 1283, 125–135 (1990)

    Google Scholar 

  2. Buba, A.T., Lee, L.S.: A differential evolution for simultaneous transit network design and frequency setting problem. Exp. Syst. Appl. 106, 277–289 (2018)

    Article  Google Scholar 

  3. Byrne, B.F.: Public transportation line positions and headways for minimum user and system cost in a radial case. Transp. Res. 9(2–3), 97–102 (1975)

    Article  Google Scholar 

  4. Chen, C.M., Chen, Y.P., Zhang, Q.: Enhancing MOEA/D with guided mutation and priority update for multi-objective optimization. In: 2009 IEEE Congress on Evolutionary Computation, May 2009, pp. 209–216 (2009)

    Google Scholar 

  5. Kitagawa, H., Sato, K., Takadama, K.: Multiagent-based sustainable bus route optimization in disaster. J. Inf. Process. 22(2), 235–242 (2014)

    Google Scholar 

  6. Majima, T., Takadama, K., Watanabe, D., Katuhara, M.: Characteristic of passenger’s route selection and generation of public transport network. SICE J. Control Measur. Syst. Integ. 8(1), 67–73 (2015)

    Article  Google Scholar 

  7. Mandl, C.E.: Evaluation and optimization of urban public transportation networks. Eur. J. Oper. Res. 5(6), 396–404 (1980)

    Article  MathSciNet  Google Scholar 

  8. Mayumi, S.: The rise of NGOs/NPOs in emergency relief in the great east Japan earthquake. Jap. Soc. Innov. J. 2(1), 26–35 (2012)

    Article  Google Scholar 

  9. Mumford, C.L.: New heuristic and evolutionary operators for the multi-objective urban transit routing problem. In: 2013 IEEE Congress on Evolutionary Computation, pp. 939–946 (2013)

    Google Scholar 

  10. Zhang, Q., Li, H.: MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712–731 (2007)

    Article  Google Scholar 

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Correspondence to Sho Kajihara .

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Kajihara, S., Sato, H., Takadama, K. (2021). Generating Duplex Routes for Robust Bus Transport Network by Improved Multi-objective Evolutionary Algorithm Based on Decomposition. In: Castillo, P.A., Jiménez Laredo, J.L. (eds) Applications of Evolutionary Computation. EvoApplications 2021. Lecture Notes in Computer Science(), vol 12694. Springer, Cham. https://doi.org/10.1007/978-3-030-72699-7_5

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  • DOI: https://doi.org/10.1007/978-3-030-72699-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72698-0

  • Online ISBN: 978-3-030-72699-7

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