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Data-driven emergency evacuation decision for cruise ports under COVID-19: An improved genetic algorithm and simulation

Author

Listed:
  • Liu, Zongtuan
  • Dong, Gang
  • Gui, Yunmiao

Abstract

With the development of the economy and the improvement of passengers’ living standards, the passenger flow of cruise ports has sharply increased. However, the outbreak of COVID-19 has introduced more emergencies. Therefore, it is of great practical significance to investigate passenger emergency evacuation from cruise ports under COVID-19 conditions. First, the dynamic control flow model of emergency evacuation is established, and a theorem is given and proven to solve the relationship between the number of optimal evacuees and optimal short circuits. Second, an improved genetic algorithm is adopted to optimize it. Third, the boarding hall of Wusong Cruise Port is used to demonstrate the theoretical model with real data. Then the evacuation time in the solution results is found to be significantly shorted. Finally, Data-driven emergency evacuation decision for cruise ports under COVID-19 is given for policy implications.

Suggested Citation

  • Liu, Zongtuan & Dong, Gang & Gui, Yunmiao, 2023. "Data-driven emergency evacuation decision for cruise ports under COVID-19: An improved genetic algorithm and simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    • Handle: RePEc:eee:phsmap:v:629:y:2023:i:c:s0378437123006490
    DOI: 10.1016/j.physa.2023.129094
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