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Hybrid large neighborhood search for the bus rapid transit route design problem

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  • Schmid, Verena

Abstract

Due to an increasing demand for public transportation and intra-urban mobility, an efficient organization of public transportation has gained significant importance in the last decades. In this paper we present a model formulation for the bus rapid transit route design problem, given a fixed number of routes to be offered. The problem can be tackled using a decomposition strategy, where route design and the determination of frequencies and passenger flows will be dealt with separately. We propose a hybrid metaheuristic based on a combination of Large Neighborhood Search (LNS) and Linear Programming (LP). The algorithm as such is iterative. Decision upon the design of routes will be handled using LNS. The resulting passenger flows and frequencies will be determined by solving a LP. The solution obtained may then be used to guide the exploration of new route designs in the following iterations within LNS. Several problem specific operators are suggested and have been tested. The proposed algorithm compares extremely favorable and is able to obtain high quality solutions within short computational times.

Suggested Citation

  • Schmid, Verena, 2014. "Hybrid large neighborhood search for the bus rapid transit route design problem," European Journal of Operational Research, Elsevier, vol. 238(2), pages 427-437.
  • Handle: RePEc:eee:ejores:v:238:y:2014:i:2:p:427-437
    DOI: 10.1016/j.ejor.2014.04.005
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    1. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    2. Ceder, Avishai & Wilson, Nigel H. M., 1986. "Bus network design," Transportation Research Part B: Methodological, Elsevier, vol. 20(4), pages 331-344, August.
    3. Laporte, Gilbert & Mesa, Juan A. & Ortega, Francisco A., 2000. "Optimization methods for the planning of rapid transit systems," European Journal of Operational Research, Elsevier, vol. 122(1), pages 1-10, April.
    4. Bussieck, Michael R. & Kreuzer, Peter & Zimmermann, Uwe T., 1997. "Optimal lines for railway systems," European Journal of Operational Research, Elsevier, vol. 96(1), pages 54-63, January.
    5. Elnaz Miandoabchi & Reza Farahani & W. Szeto, 2012. "Bi-objective bimodal urban road network design using hybrid metaheuristics," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(4), pages 583-621, December.
    6. Agostino Nuzzolo & Francesco Russo & Umberto Crisalli, 2001. "A Doubly Dynamic Schedule-based Assignment Model for Transit Networks," Transportation Science, INFORMS, vol. 35(3), pages 268-285, August.
    7. Verena Schmid & Karl F. Doerner, 2014. "Examination and Operating Room Scheduling Including Optimization of Intrahospital Routing," Transportation Science, INFORMS, vol. 48(1), pages 59-77, February.
    8. Jan-Willem Goossens & Stan van Hoesel & Leo Kroon, 2004. "A Branch-and-Cut Approach for Solving Railway Line-Planning Problems," Transportation Science, INFORMS, vol. 38(3), pages 379-393, August.
    9. Claessens, M. T. & van Dijk, N. M. & Zwaneveld, P. J., 1998. "Cost optimal allocation of rail passenger lines," European Journal of Operational Research, Elsevier, vol. 110(3), pages 474-489, November.
    10. Guihaire, Valérie & Hao, Jin-Kao, 2008. "Transit network design and scheduling: A global review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1251-1273, December.
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    Cited by:

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    3. Blum, Christian & Ochoa, Gabriela, 2021. "A comparative analysis of two matheuristics by means of merged local optima networks," European Journal of Operational Research, Elsevier, vol. 290(1), pages 36-56.
    4. Cancela, Héctor & Mauttone, Antonio & Urquhart, María E., 2015. "Mathematical programming formulations for transit network design," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 17-37.
    5. Alberto Santini & Stefan Ropke & Lars Magnus Hvattum, 2018. "A comparison of acceptance criteria for the adaptive large neighbourhood search metaheuristic," Journal of Heuristics, Springer, vol. 24(5), pages 783-815, October.

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