Optimal Route Planning for Dynamic Experience Based on TOMM Theory Application Innovation: a Case Study of the Three-River-Source National Park

WANG Jia-xin; CHEN Zhuo; ZHANG Yu-jun

doi:10.13931/j.cnki.bjfuss.2021087

Journal of Beijing Forestry University (Social Science) > 2021 > 20(2): 53-58. > DOI: 10.13931/j.cnki.bjfuss.2021087

WANG Jia-xin, CHEN Zhuo, ZHANG Yu-jun. Optimal Route Planning for Dynamic Experience Based on TOMM Theory Application Innovation: a Case Study of the Three-River-Source National Park[J]. Journal of Beijing Forestry University (Social Science), 2021, 20(2): 53-58. DOI: 10.13931/j.cnki.bjfuss.2021087

Citation:

PDF (609 KB)

Optimal Route Planning for Dynamic Experience Based on TOMM Theory Application Innovation: a Case Study of the Three-River-Source National Park

1.
School of Landscape Architecture, Beijing Forestry University, 100083, P. R. China
2.
School of Artifical Intelligence, University of Chinese Academy of Sciences, 100049, P. R. China

More Information

Received Date: April 19, 2021
Available Online: June 21, 2021
Published Date: June 29, 2021

Graphical Abstract

Abstract

Abstract

The visitor's recreational experience is a multi-stage experience process, including anticipation, on-site travel, on-site participation, departure from the site, and recall. At present, the entire tourism industry and related infrastructure are undergoing digitization, and tourism digitization is called e-tourism. In the future, e-tourism will extend to the entire travel cycle, and nature tourism in protected areas is no exception. This article mainly adopt sinter disciplinary exploratory research methods such as literature review, field investigation, expert scoring, and mathematical modeling to innovate the application model of the visitor recreation management tool in the traditional protected area—Tourism Optimization Management Model (TOMM theory). Taking the Three-River-Source National Park as a case, we use artificial intelligence algorithms to solve the core problem of visitors with different recreational needs—"customized optimal route planning with dynamic experience". With this as the core, it is possible to build a practical scenario for the application of TOMM theory in the context of e-tourism, that is, to realize the application of TOMM theory in the national park application scenario. TOMM theory is based on the application mode of "customized optimal route planning with dynamic experience" APP in the context of smart national parks, which will solve the two major practical difficulties in traditional TOMM theory, that is, it is difficult to control the way and degree of public active participation, and it is difficult to obtain and monitor real-time data streams. At the same time, the research will provide a research foundation for the establishment of the smart protected area system with Chinese characteristics.
- TOMM,
- public participation,
- tourism monitoring,
- AI algorithm intelligent visitor routes,
- national park APP

FullText(HTML)

References (31)

References

[1]	本刊编辑部. 《关于建立以国家公园为主体的自然保护地体系指导意见》发布[J]. 绿色中国,2020(1):31.
[2]	CLARK R, STANKEY G. The recreation opportunity spectrum: a framework for planning, management, and research[R]. Washington DC: USDA Forest Service General Technical Report, 1979.
[3]	GRAEFE A R, KUSS F R, VASKE J J. Visitor impact management: the planning framework[M]. Washington DC: National Parks and Conservation Association, 1990.
[4]	STANKEY G H, COLE D N, LUCAS R C, et al. The limits of acceptable change （LAC） system for wilderness planning[M]. Ogden: USDA, Forest Service, Intermountain Forest and Range Experiment Station, 1985.
[5]	National Park Service. VERP: visitor experience and resource protection framework[M]. Denver: US Department of Interior, National Park Service Denver, Service Center, 1997.
[6]	GRAHAM R,NILSEN P,PAYNE R J. Visitor management in Canadian national parks[J]. Tourism Management,1988,9(1):44-61. doi: 10.1016/0261-5177(88)90057-X
[7]	Manidis Roberts Consultants. Developing a tourism optimisation management model （TOMM）[R]. New South Wales: Manidis Roberts Consultants, 1997.
[8]	NEWSOME D, MOORE S, DOWLING R. Natural area tourism: ecology, impacts and management[M]. New York: Channel View Publications, 2013.
[9]	JIRICKA A,SALAK B,ARNBERGER A,et al. VV-TOMM:capacity building in remote tourism territories through the first European transnational application of the tourism optimization management model[J]. WIT Transactions on Ecology and the Environment,2014,187:93-103.
[10]	MAC K K. Developing community tourism in Uganda, the tourism optimization management mode[R]. Kampala: Makerere University & University of Manitoba CIDA Project, Workshop Report on Community Tourism Development Framework in Uganda , 2007.
[11]	BROWN G,WEBER D. Using public participation GIS (PPGIS) on the geo-web to monitor tourism development preferences[J]. Journal of Sustainable Tourism,2013,21(2):192-211.
[12]	MOORE S,SMITHA J,NEWSOME D N. Environmental performance reporting for natural area tourism:contributions by visitor impact management frameworks and their indicators[J]. Journal of Sustainable Tourism,2003,11(4):348-375. doi: 10.1080/09669580308667211
[13]	BROWN G, KOTH B, KREAG G, et al. Managing Australia's protected areas, a review of visitor management models, frameworks and processes[R]. Gold Coast: Sustainable Tourism Cooperative Research Centre（CRC), 2006.
[14]	WOLF J. Using GPS data loggers to replace travel diaries in the collection of travel data[D]. Atlanta : Georgia Institute of Technology, 2000.
[15]	SHOVAL N,ISAACSON M,CHHETRI P. GPS,smartphones,and the future of tourism research[J]. The Wiley Blackwell Companion to Tourism,2014,31:251-261.
[16]	STOPHER P R,GREAVES S P. Household travel surveys:where are we going?[J]. Transportation Research Part A:Policy and Practice,2007,41(5):367-381. doi: 10.1016/j.tra.2006.09.005
[17]	ORELLANA D,BREGT A K. Exploring visitor movement patterns in natural recreational areas[J]. Tourism Management,2012,33(3):672-682. doi: 10.1016/j.tourman.2011.07.010
[18]	GRINBERGER A Y,SHOVAL N. Typologies of tourists' time-space consumption:a new approach using GPS data and GIS tools[J]. Tourism Geographies,2014,16(1):105-123. doi: 10.1080/14616688.2013.869249
[19]	SHOVAL N,AHAS R. The use of tracking technologies in tourism research:the first decade[J]. Tourism Geographies,2016,18(5):587-606. doi: 10.1080/14616688.2016.1214977
[20]	DOAN A,RAMAKRISHNAN R,HALEVY A Y. Crowd sourcing systems on the world-wide web[J]. Communications of the ACM,2011,54(4):86. doi: 10.1145/1924421.1924442
[21]	LEVIN N,LECHNER A M,BROWN G. An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas[J]. Applied Geography,2017,79:115-126. doi: 10.1016/j.apgeog.2016.12.009
[22]	WOOD S,GUERRY A,SILVER J,et al. Using social media to quantify nature-based tourism and recreation[J]. Scientific Reports,2013,3(1):1-7.
[23]	游兮. 多元创新的规划公众参与政策及模式探索[J]. 低碳世界,2016(21):163-164.
[24]	BIRENBOIM A,SHOVAL N. Mobility research in the age of the smartphone[J]. Annals of the American Association of Geographers,2016,106(2):283-291.
[25]	樊守伟,严艳,张少杰,等. Dijkstra算法与旅游路径优化[J]. 西安邮电大学学报,2014(1):121-124.
[26]	袁光辉,谢科,邓林胜,等. 旅游路线动态规划问题研究−以西安市出发为例[J]. 数学的实践与认识,2016,46(15):125-133.
[27]	余明朗. 面向景区智能导游的室内外一体化定位及位置服务方法研究[D]. 南京: 南京师范大学, 2013.
[28]	胡军国,祁亨年,董峰,等. 一种改进蚁群算法研究和旅游景区路径规划问题求解[J]. 计算机应用研究,2011,28(5):1647-1650. doi: 10.3969/j.issn.1001-3695.2011.05.014
[29]	刘倩,卫文学,张鲁. 改进蚁群算法在景区路径规划中的应用研究[J]. 信息技术与信息化,2012(6):56-59. doi: 10.3969/j.issn.1672-9528.2012.06.14
[30]	徐锋,杜军平. 改进蚁群算法在旅游路线规划中的应用研究[J]. 计算机工程与应用,2009,45(23):193,195,226.
[31]	周啸,李胜辉,高奎亮,等. 一种多约束指标改进的动态旅游路线规划算法[J]. 中北大学学报(自然科学版),2019,40(1):63-68,75.

Cited By

Get Citation

PDF

XML

Article views (823) PDF downloads (53)

Turn off MathJax

Article Contents

Abstract

References

Optimal Route Planning for Dynamic Experience Based on TOMM Theory Application Innovation: a Case Study of the Three-River-Source National Park

Abstract

References

Catalog

Export File

Citation

Format

Content