Mass Evacuation Transportation Model Using Hybrid Genetic Algorithm

Dahlan Abdullah, Herman Fithra


The process of evacuating natural disasters requires careful planning. In particular, the evacuation process needs attention in the evacuation process because it involves the safety of many people. Evacuation time itself depends on information about incomplete evacuation routes such as those concerning desired velocity and obstacle parameters. When viewed in terms of transportation planning for evacuation, it is an Auto-Based Evacuation Model problem where the community, in this case, drivers, certainly do not know the evacuation planning or the route they will go through because, in the event of a disaster, it cannot be predicted which areas will be affected. The routing problem can be viewed as a discrete problem where the traffic problem is following a user equilibrium model. It has a bi-level structure. Top-level is used to minimize evacuation time using the contraflow strategy. At the same time, traffic volume and travel time are modeled at a low level. This problem is a linear programming problem whose solution will be optimized using a Hybrid Genetic Algorithm. This model is proposed to carry out mass evacuation processes based on time-window constraints. Finally, computational results are provided to demonstrate the validity and robustness of the proposed model. Based on the test results, it can be seen that the designed model can adjust the path that the vehicle follows with the vehicle station by adjusting the available capacity. The results showed that the intended route provided by the model was the shortest route.


Transportation planning; auto-based evacuation model; linear programming; hybrid genetic algorithm.

Full Text:



H. Gao, B. Medjdoub, H. Luo, H. Zhong, B. Zhong, and D. Sheng, “Building evacuation time optimization using constraint-based design approach,†Sustain. Cities Soc., vol. 52, p. 101839, Jan. 2020, doi: 10.1016/j.scs.2019.101839.

Q. Li, Y. Gao, L. Chen, and Z. Kang, “Emergency evacuation with incomplete information in the presence of obstacles,†Phys. Stat. Mech. Its Appl., vol. 533, p. 122068, Nov. 2019, doi: 10.1016/j.physa.2019.122068.

D. Brezina, L. Šimák, M. Hudáková, and M. Masár, “Comparison of transport problems in process of evacuation,†Transp. Res. Procedia, vol. 40, pp. 970–977, Jan. 2019, doi: 10.1016/j.trpro.2019.07.136.

Nicklow John et al., “State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management,†J. Water Resour. Plan. Manag., vol. 136, no. 4, pp. 412–432, Jul. 2010, doi: 10.1061/(ASCE)WR.1943-5452.0000053.

J. Hua, G. Ren, Y. Cheng, and B. Ran, “An Integrated Contraflow Strategy for Multimodal Evacuation,†Mathematical Problems in Engineering, 2014. (accessed Oct. 06, 2019).

X. Gao, M. K. Nayeem, and I. M. Hezam, “A robust two-stage transit-based evacuation model for large-scale disaster response,†Measurement, vol. 145, pp. 713–723, Oct. 2019, doi: 10.1016/j.measurement.2019.05.067.

Y. Jiang, Y. Yuan, K. Huang, and L. Zhao, “Logistics for Large-Scale Disaster Response: Achievements and Challenges,†45th Hawaii Int. Conf. Syst. Sci. HICSS, pp. 1277–1285, Jan. 2012, doi: 10.1109/HICSS.2012.418.

W. Engelbach, S. Frings, R. Molarius, C. Aubrecht, M. Meriste, and A. Perrels, “Indicators to compare simulated crisis management strategies,†in Proceedings of the International Disaster and Risk Conference : IDRC DAVOS 2014. Extended abstracts, Oral presentations, Special Panels, Sessions and Workshops, 2014, pp. 225–228, Accessed: Oct. 06, 2019. [Online]. Available:

V. C. Pereira and D. R. Bish, “Scheduling and Routing for a Bus-Based Evacuation with a Constant Evacuee Arrival Rate,†Transp. Sci., vol. 49, no. 4, pp. 853–867, Oct. 2014, doi: 10.1287/trsc.2014.0555.

M. Goerigk, B. Grün, and P. Heßler, “Branch and bound algorithms for the bus evacuation problem,†Comput. Oper. Res., vol. 40, no. 12, pp. 3010–3020, Dec. 2013, doi: 10.1016/j.cor.2013.07.006.

R. Swamy, J. E. Kang, R. Batta, and Y. Chung, “Hurricane evacuation planning using public transportation,†Socioecon. Plann. Sci., vol. 59, pp. 43–55, Sep. 2017, doi: 10.1016/j.seps.2016.10.009.

A.-N. Qazi, Y. Nara, K. Okubo, and H. Kubota, “Demand variations and evacuation route flexibility in short-notice bus-based evacuation planning,†IATSS Res., vol. 41, no. 4, pp. 147–152, Dec. 2017, doi: 10.1016/j.iatssr.2017.01.002.

J. C. Chu, A. Y. Chen, and Y.-F. Lin, “Variable guidance for pedestrian evacuation considering congestion, hazard, and compliance behavior,†Transp. Res. Part C Emerg. Technol., vol. 85, pp. 664–683, Dec. 2017, doi: 10.1016/j.trc.2017.10.009.

Y. Wang and J. Wang, “Integrated reconfiguration of both supply and demand for evacuation planning,†Transp. Res. Part E Logist. Transp. Rev., vol. 130, pp. 82–94, Oct. 2019, doi: 10.1016/j.tre.2019.08.016.

S. Bingfeng, Z. Ming, Y. Xiaobao, and G. Ziyou, “Bi-level Programming Model for Exclusive Bus Lanes Configuration in Multimodal Traffic Network,†Transp. Res. Procedia, vol. 25, pp. 652–663, Jan. 2017, doi: 10.1016/j.trpro.2017.05.449.

G. Londono and A. Lozano, “A Bilevel Optimization Program with Equilibrium Constraints for an Urban Network Dependent on Time,†Transp. Res. Procedia, vol. 3, pp. 905–914, Jan. 2014, doi: 10.1016/j.trpro.2014.10.070.

C. C. Liu, S. W. Chu, Y. K. Chan, and S. S. Yu, “A Modified K-Means Algorithm - Two-Layer K-Means Algorithm,†in 2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Aug. 2014, pp. 447–450, doi: 10.1109/IIH-MSP.2014.118.

M. Z. Islam, V. Estivill-Castro, M. A. Rahman, and T. Bossomaier, “Combining K-Means and a genetic algorithm through a novel arrangement of genetic operators for high quality clustering,†Expert Syst. Appl., vol. 91, pp. 402–417, Jan. 2018, doi: 10.1016/j.eswa.2017.09.005.

A. K. Junior, “Analisis Pengaruh Metode Crossover dan Seleksi terhadap Performa Algoritma GenClust++,†Thesis, Bina Nusantara, Jakarta, 2018.



  • There are currently no refbacks.

Published by INSIGHT - Indonesian Society for Knowledge and Human Development