Abstract
This research addresses the problem of planning tourism routes and finding appropriate shopping (market place) locations for agricultural product transportation. Generally, tourists visit popular tourism attractions; and generally, unpopular tourism attractions do not stimulate the economy, trade, or local income. Popular tourism attractions that are located far away from each other require the transportation of local products, and tourists must make decisions as to which locations to visit when planning their vacation. Planning a tourism route while balancing tourism attractions and shopping markets is important for the economic stimulation of tourism. This work presents a problem-solving method for tourism route-planning for a particular case study in Chiang Rai province, Thailand, using the Adaptive Large Neighborhood Search (ALNS) method. Six main destruction and five repair cycles in the ALNS method were applied to solve the tourism route design problem and to find the best solution so that tourists can visit all of the main attractions. We found that 13 tourism routes provide the shortest travel distance for each travel route. The total distance traveled was 2538.02 km for all routes. To balance the tourism on all routes, the popular and less popular tourism attractions were combined. For all routes, the shopping market location is the best place for tourism products to be sold and where tourist relaxation occurs. The results from ALNS were compared with the results from those obtained by the exact Lingo program V11. The ALNS algorithm results were not significantly different from the Lingo results. For the computational results for all examined cases, the ALNS algorithm was shown to be competitive, with short processing times given the sizes of the problems. For the traveling distance, the ALNS result significantly differs from the exact method by approximately 1.12%, and had a better effect than the exact method by approximately 99% in terms of processing time. Therefore, the proposed methodology provides an effective and high-quality solution for tourism route planning.
Highlights
Tourism management planning is an important challenge in sustainable tourism development.Tourism promotion is a strategy of tourism development that encourages economic development and income for the host country
Many popular tourism attractions are crowded with tourists due to these attractions being promoted by tourism organizations
The Lingo program and Adaptive Large Neighborhood Search (ALNS) algorithm were run on a computer with Intel® CoreTM i5-2320M
Summary
Tourism management planning is an important challenge in sustainable tourism development. The design of the tourism route and selection of suitable shopping market locations is important in the development of local trade and tourism attractions These two aspects are planning problems that require information from tourism organizations and tourists (Nagy and Salhi 2007). Marketplace allocation is necessary for tourism trip design for stimulating local economic development and determining tourism routes The shortage of both tourism planning and locations that facilitate tourism has resulted in tourists being unable to visit all the tourism attractions within their time limit, which may negatively influence the satisfaction of tourists (Lumsdon and Stephen 2004; Zheng et al 2017). The results of and discussion about the Adaptive Large Neighborhood Search algorithm are provided in Section 5, and Section 6 provides our conclusions
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