{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/190409352","title":"Donkey and Smuggler Optimization Algorithm: A Collaborative Working Approach to Path Finding","arxiv_id":"1904.09352","date":"2019-04-19","proceeding":null,"authors":["Ahmed S. Shamsaldin","Tarik A. Rashid","Rawan A. Al-Rashid Agha","Nawzad K. Al-Salihi","Mokhtar Mohammadi"],"abstract":"Swarm Intelligence is a metaheuristic optimization approach that has become\nvery predominant over the last few decades. These algorithms are inspired by\nanimals' physical behaviors and their evolutionary perceptions. The simplicity\nof these algorithms allows researchers to simulate different natural phenomena\nto solve various real-world problems. This paper suggests a novel algorithm\ncalled Donkey and Smuggler Optimization Algorithm (DSO). The DSO is inspired by\nthe searching behavior of donkeys. The algorithm imitates transportation\nbehavior such as searching and selecting routes for movement by donkeys in the\nactual world. Two modes are established for implementing the search behavior\nand route-selection in this algorithm. These are the Smuggler and Donkeys. In\nthe Smuggler mode, all the possible paths are discovered and the shortest path\nis then found. In the Donkeys mode, several donkey behaviors are utilized such\nas Run, Face & Suicide, and Face & Support. Real world data and applications\nare used to test the algorithm. The experimental results consisted of two\nparts, firstly, we used the standard benchmark test functions to evaluate the\nperformance of the algorithm in respect to the most popular and the state of\nthe art algorithms. Secondly, the DSO is adapted and implemented on three\nreal-world applications namely; traveling salesman problem, packet routing, and\nambulance routing. The experimental results of DSO on these real-world problems\nare very promising. The results exhibit that the suggested DSO is appropriate\nto tackle other unfamiliar search spaces and complex problems.","url_abs":"http://arxiv.org/abs/1904.09352v1","url_pdf":"http://arxiv.org/pdf/1904.09352v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"190409352","repo_url":"https://github.com/Charan619/Get-me-there","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"190409352","repo_url":"https://github.com/Tarik4Rashid4/DSO","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"metaheuristic-optimization","task_name":"Metaheuristic Optimization"},{"task_slug":"traveling-salesman-problem","task_name":"Traveling Salesman Problem"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}