An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas
The expansion of the tourism industry has led to the development of various methods to find optimal tourism paths. However, planning tourism paths in hilly areas remains complex and has specific challenges. Different algorithms have been used to plan tourism paths in flat and hilly terrains, includi...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/14/1/34 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832588364721684480 |
|---|---|
| author | Mohamed A. Damos Wenbo Xu Jun Zhu Ali Ahmed Abdolraheem Khader |
| author_facet | Mohamed A. Damos Wenbo Xu Jun Zhu Ali Ahmed Abdolraheem Khader |
| author_sort | Mohamed A. Damos |
| collection | DOAJ |
| description | The expansion of the tourism industry has led to the development of various methods to find optimal tourism paths. However, planning tourism paths in hilly areas remains complex and has specific challenges. Different algorithms have been used to plan tourism paths in flat and hilly terrains, including the traditional Ant Colony Optimization (ACO). Although widely used, this algorithm faces a number of limitations due to its slow implementation and pheromone update rules. This paper introduces a new approach to overcome these limitations. It presents a method for efficiently optimizing tourism paths in hilly areas based on an improved version of the ACO algorithm. The limitations of the traditional ACO and the Genetic Algorithm (GA) are addressed by improving pheromone updating techniques and implementing new initialization parameters. This approach provides a comprehensive and efficient method for planning hiking trails in hilly regions, considering dynamic tourism objectives such as temperature, atmospheric pressure, and health status. The proposed method is implemented to develop tourist routes in the hilly Jebel Marra region in Western Sudan. A comparison is provided between the effectiveness of this approach and the GA and traditional ACO algorithms. The advantage of the proposed approach is illustrated by results showing an optimization time of 0 points and 27 s compared to 0 points and 45 s and 0 points and 40 s for GA and ACO, respectively. |
| format | Article |
| id | doaj-art-a96a0509b7ee4cfdb487e8674bcb9f10 |
| institution | Kabale University |
| issn | 2220-9964 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj-art-a96a0509b7ee4cfdb487e8674bcb9f102025-01-24T13:35:03ZengMDPI AGISPRS International Journal of Geo-Information2220-99642025-01-011413410.3390/ijgi14010034An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly AreasMohamed A. Damos0Wenbo Xu1Jun Zhu2Ali Ahmed3Abdolraheem Khader4School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 610054, ChinaSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 610054, ChinaFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, ChinaFaculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Xuanwu District, Nanjing 210094, ChinaThe expansion of the tourism industry has led to the development of various methods to find optimal tourism paths. However, planning tourism paths in hilly areas remains complex and has specific challenges. Different algorithms have been used to plan tourism paths in flat and hilly terrains, including the traditional Ant Colony Optimization (ACO). Although widely used, this algorithm faces a number of limitations due to its slow implementation and pheromone update rules. This paper introduces a new approach to overcome these limitations. It presents a method for efficiently optimizing tourism paths in hilly areas based on an improved version of the ACO algorithm. The limitations of the traditional ACO and the Genetic Algorithm (GA) are addressed by improving pheromone updating techniques and implementing new initialization parameters. This approach provides a comprehensive and efficient method for planning hiking trails in hilly regions, considering dynamic tourism objectives such as temperature, atmospheric pressure, and health status. The proposed method is implemented to develop tourist routes in the hilly Jebel Marra region in Western Sudan. A comparison is provided between the effectiveness of this approach and the GA and traditional ACO algorithms. The advantage of the proposed approach is illustrated by results showing an optimization time of 0 points and 27 s compared to 0 points and 45 s and 0 points and 40 s for GA and ACO, respectively.https://www.mdpi.com/2220-9964/14/1/34tourism industryhilly areastraveling salesman problemdynamic tourism objectivesant colony optimization |
| spellingShingle | Mohamed A. Damos Wenbo Xu Jun Zhu Ali Ahmed Abdolraheem Khader An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas ISPRS International Journal of Geo-Information tourism industry hilly areas traveling salesman problem dynamic tourism objectives ant colony optimization |
| title | An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas |
| title_full | An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas |
| title_fullStr | An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas |
| title_full_unstemmed | An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas |
| title_short | An Efficient Tourism Path Approach Based on Improved Ant Colony Optimization in Hilly Areas |
| title_sort | efficient tourism path approach based on improved ant colony optimization in hilly areas |
| topic | tourism industry hilly areas traveling salesman problem dynamic tourism objectives ant colony optimization |
| url | https://www.mdpi.com/2220-9964/14/1/34 |
| work_keys_str_mv | AT mohamedadamos anefficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT wenboxu anefficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT junzhu anefficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT aliahmed anefficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT abdolraheemkhader anefficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT mohamedadamos efficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT wenboxu efficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT junzhu efficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT aliahmed efficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas AT abdolraheemkhader efficienttourismpathapproachbasedonimprovedantcolonyoptimizationinhillyareas |