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计算机技术21年22期

基于蚁群算法的博物馆人流动线设计研究
贺嘉琦,高子期
(西安工程大学,陕西 西安 710048)

摘  要:为优化博物馆人流动线设计的合理性,提高游客在博物馆中的参观体验感,文章提出通过蚁群算法对博物馆的人流动线设计进行研究。以秦始皇兵马俑博物馆为例,用栅格图法对秦始皇兵马俑博物馆的人流动线进行相关实验研究。经过三种仿真模拟实验,模拟五个展馆在特殊情况下多种开馆情况。通过更新信息素和增加迭代次数来判断人流动线的长短,得出秦始皇兵马俑博物馆人流动线的最短路径和参观顺序。仿真实验证明,蚁群算法可用于秦始皇兵马俑博物馆三种参观需求的人流动线规划设计。蚁群算法在博物馆的人流动线设计中是有效的,可以得出一种最优的参观人流动线设计规划。


关键词:博物馆;蚁群算法;人流动线设计;参观顺序;最短路径



DOI:10.19850/j.cnki.2096-4706.2021.22.023


中图分类号:TP18;TU242.5                           文献标识码:A                                  文章编号: 2096-4706(2021)22-0079-04


Research on Design of Museum People Flow Line Based on Ant Colony Algorithm

HE Jiaqi,GAO Ziqi

(Xi’an Polytechnic University, Xi’an 710048, China)

Abstract: In order to optimize the rationality of the design of people flow line in the museum to improve visitors’ visiting experience in the museum. This paper proposes to study the design of people flow line of museum through ant colony algorithm. Taking the Terracotta Warriors and Horses Museum of Qin Shihuang as an example, this paper makes an experimental study on the people flow line of the Terracotta Warriors and Horses Museum of Qin Shihuang by using the grid method. After three kinds of simulation experiments, simulate the opening of five pavilions under special circumstances. By updating the pheromone and increasing the number of iterations to judge the length of the people flow line, the shortest path and visiting order of the people flow line in the Terracotta Warriors and Horses Museum of Qin Shihuang are obtained. Simulation results show that the ant colony algorithm can be used for the planning and design of people flow lines for three visiting needs of the Terracotta Warriors and Horses Museum of Qin Shihuang. Ant colony algorithm is effective in the design of people flow line of Museum, and an optimal design plan of visitor flow line can be obtained.

Keywords: museum; ant colony algorithm; people flow line design; visiting order; shortest path


参考文献:

[1] 陶重犇,雷祝兵,李春光,等 . 基于改进模拟退火算法的搬运机器人路径规划 [J]. 计算机测量与控制,2018,26(7): 182-185.

[2] 陈亚琳,庄丽阳,朱龙彪,等 . 基于改进 Dijkstra 算法的泊车系统路径规划研究 [J]. 现代制造工程,2017(8):63-67.

[3] CHOI M, CHUNG H, YAMAGUCHI H, et al. Arctic sea route path planning based on an uncertain ice prediction model [J].Cold Regions Science and Technology, 2015,109:61-69.

[4] 孙丰财,张亚楠,史旭华 . 改进的快速扩展随机树路径规划算法 [J]. 传感器与微系统,2017,36(9):129-131+135.

[5] 刘志海,薛媛,周晨,等 . 基于遗传算法的机器人路径规划的种群初始化改进 [J]. 机床与液压,2019,47(21):5-8.

[6] DORIGO M,GAMBARDELLA L M. Ant colony system: a cooperative learning approach to the traveling salesman problem [J].IEEE Transactions onEvolutionary Computation,1997,1(1):53-66.

[7] 郭保青,郝树运,朱力强,等 . 基于改进蚁群算法的多 AGV 泊车路径规划 [J]. 交通运输系统工程与信息,2018,18(6): 55-62+80.

[8] 王雷,石鑫 . 基于改进蚁群算法的移动机器人动态路径规划 [J]. 南京理工大学学报,2019,43(6):700-707.

[9] 施建礼,刘志浩,潘爽 . 蚁群算法的路径规划改进策略 [J]. 火力与指挥控制,2019,44(10):153-157+162.

[10] 杨海荣,阎磊 . 论博物馆建筑内部的交通流线设计 [J]. 四川建筑科学研究,2009,35(5):210-214.

[11] 王志中 . 基于改进蚁群算法的移动机器人路径规划研究 [J]. 机械设计与制造,2018(1):242-244.

[12] LONG Z Q. Dynamic path planning of mobile robot based on ant colony algorithm [J].International Journal of Reasoning-based Intelligent Systems,2018,10(2):122-127.

[13] LUO Q,WANG H B,ZHENG Y,et al. Research on path planning of mobile robot based on improved ant colony algorithm [J]. Neural Computing & Applications,2020,32(6):1555-1566.

[14] 程向红,祁艺 . 基于栅格法的室内指示路径规划算法 [J]. 中国惯性技术学报,2018,26(2):236-240+267.


作者简介:贺嘉琦(1995—),男,汉族,山西太原人,硕士研究生在读,研究方向:环境艺术设计理论与实践研究。通讯作者: 高子期(1974—),女,汉族,四川雅安人,副教授,博士,研究方向: 艺术考古。