{"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/solving-the-clustered-traveling-salesman","title":"Solving the clustered traveling salesman problem with d-relaxed priority rule","arxiv_id":"1810.03981","date":"2018-10-06","proceeding":null,"authors":["Hoa Nguyen Phuong","Huyen Tran Ngoc Nhat","Minh Hoàng Hà","André Langevin","Martin Trépanier"],"abstract":"The Clustered Traveling Salesman Problem with a Prespecified Order on the\nClusters, a variant of the well-known traveling salesman problem is studied in\nliterature. In this problem, delivery locations are divided into clusters with\ndifferent urgency levels and more urgent locations must be visited before less\nurgent ones. However, this could lead to an inefficient route in terms of\ntraveling cost. This priority-oriented constraint can be relaxed by a rule\ncalled d-relaxed priority that provides a trade-off between transportation cost\nand emergency level. Our research proposes two approaches to solve the problem\nwith d-relaxed priority rule. We improve the mathematical formulation proposed\nin the literature to construct an exact solution method. A meta-heuristic\nmethod based on the framework of Iterated Local Search with problem-tailored\noperators is also introduced to find approximate solutions. Experimental\nresults show the effectiveness of our methods.","url_abs":"http://arxiv.org/abs/1810.03981v1","url_pdf":"http://arxiv.org/pdf/1810.03981v1.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":"solving-the-clustered-traveling-salesman","repo_url":"https://github.com/beyzak-stack/Beyza-Keskin","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"traveling-salesman-problem","task_name":"Traveling Salesman Problem"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}