Path Planning of Coastal Tourism Based on the Improved Firefly Algorithm

Abstract

Zhou, X., 2020. Path planning of coastal tourism based on the improved firefly algorithm. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 263–266. Coconut Creek (Florida), ISSN 0749-0208.To optimize the path of coastal tourism, a niche firefly algorithm (NFA) is proposed. First, according to the characteristics of environment, a reasonable path-planning model is established, and the objective function of the firefly algorithm (FA) is set as moving steps. It has redesigned the brightness formula, initialization method, and firefly movement mode. Second, on the basis of the FA, the introduction of niche technology needs to join the shared information among niche populations. Simulation experiments show that NFA can get several optimal operations compared with FA; the average number of moving steps decreased by 7.14%, and the objective function of NFA decreased by 6.76%. The average value of firefly brightness has increased by 8.33%. Compared with the genetic algorithm, NFA's moving steps have decreased by 7.14%, and the mean of objective function decreased by 9.79%. The results show that NFA is better in algorithm performance.