Discrete Robustness Optimization on Emergency Transportation Network Based on Prospect Theory

Autor: Zheng-kun Zhang, Chang-feng Zhu, Qing-rong Wang, Jia-shan Yuan
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Journal of Advanced Transportation, Vol 2019 (2019)
Druh dokumentu: article
ISSN: 0197-6729
2042-3195
DOI: 10.1155/2019/2728073
Popis: This paper focuses on the discrete robustness optimization of emergency transportation network with the consideration of timeliness and decision behavior of decision-maker under the limited rationality. Based on a situation that the nearer to disaster area, the higher probability of time delay, prospect theory is specially introduced to reflect the subjective decision behavior of decision-maker. Then, a discrete robustness optimization model is proposed with the purpose of the better timeliness and robustness. The model is based on the emergency transportation network with multistorage centers and multidisaster points. In order to obtain the optimal solution, an improved genetic algorithm is designed by introducing a bidirectional search strategy based on a newfangled path cluster to obtain specific paths that connect each storage centers and each disaster points. Finally, a case study is exhibited to demonstrate the reasonability of the model, theory, and algorithm. The result shows that the path cluster with the better timeliness and robustness can be well obtained by using the prospect theory and improved genetic algorithm. The analysis especially reveals that the robustness is correspondent to the risk aversion in prospect theory.
Databáze: Directory of Open Access Journals
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