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Article type: Research Article
Authors: Zhai, Longzhen | Feng, Shaohong; *
Affiliations: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Correspondence: [*] Corresponding author. Shaohong Feng, College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Postal code 210016, Jiangsu, China. E-mail: [email protected].
Abstract: In order to solve the problem of finding the best evacuation route quickly and effectively, in the event of an accident, a novel evacuation route planning method is proposed based on Genetic Algorithm and Simulated Annealing algorithm in this paper. On the one hand, the simulated annealing algorithm is introduced and a simulated annealing genetic algorithm is proposed, which can effectively avoid the problem of the search process falling into the local optimal solution. On the other hand, an adaptive genetic operator is designed to achieve the purpose of maintaining population diversity. The adaptive genetic operator includes an adaptive crossover probability operator and an adaptive mutation probability operator. Finally, the path planning simulation verification is carried out for the genetic algorithm and the improved genetic algorithm. The simulation results show that the improved method has greatly improved the path planning distance and time compared with the traditional genetic algorithm.
Keywords: Genetic Algorithm (GA), stimulated annealing (SA), adaptive Algorithm, evacuation
DOI: 10.3233/JIFS-211214
Journal: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1813-1823, 2022
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