Abstract
As one of the most critical components in disaster relief operations, emergency transportation planning often involves huge amount of relief goods, complex hybrid transportation networks, and complex constraints. In this paper, we present a new emergency transportation planning model which combines rail and road transportation and supports transfer between the two modes. For solving the problem, we propose a novel hybrid algorithm that integrates two meta-heuristics, water wave optimization (WWO) and particle swarm optimization (PSO), whose operators are elaborately adapted to effectively balance the exploration and exploitation of the search space. Experimental results show that the performance of our method is better than a number of well-known heuristic algorithms on test instances.
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This work is supported by National Natural Science Foundation (Grant No. 61473263) of China.
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Rong, ZY., Zhang, MX., Du, YC., Zheng, YJ. (2018). A Hybrid Evolutionary Algorithm for Combined Road-Rail Emergency Transportation Planning. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_44
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DOI: https://doi.org/10.1007/978-3-319-93815-8_44
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