A comprehensive survey on the generalized traveling salesman problem

• Published in: European journal of operational research Vol. 314; no. 3; pp. 819 - 835
• Main Authors: Pop, Petrică C., Cosma, Ovidiu, Sabo, Cosmin, Sitar, Corina Pop
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2024
• Subjects: Combinatorial optimization; Generalized traveling salesman problem; Heuristic and metaheuristic algorithms; Mathematical formulations; Traveling salesman problem; Traveling salesman problem; Generalized traveling salesman problem; Combinatorial optimization; Mathematical formulations; Heuristic and metaheuristic algorithms
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2023.07.022

•We provide a comprehensive survey on the Generalized Traveling Salesman Problem.•We present a comparative analysis of the performance of the state-of-the-art algorithms.•We discuss certain open problems and potential research directions. The generalized traveling salesman problem (GTSP) is an extension of the classical traveling salesman problem (TSP) and it is among the most researched combinatorial optimization problems due to its theoretical properties, complexity aspects and real-life applications in various areas: location-routing problems, material flow design problem, distribution of medical supplies, urban waste collection management, airport selection and routing the courier airplanes, image retrieval and ranking, digital garment manufacturing, etc. Even though the importance of this combinatorial optimization problem was highlighted in several publications and there were developed several methods for solving it, there is no survey dedicated to the GTSP. The scope of this paper is to close this gap by providing a comprehensive survey on mathematical formulations, solution approaches and latest advances regarding the GTSP. The paper is organized around the following issues: problem definition, variations and related problems, real-life applications of the GTSP, mathematical formulations, solution approaches designed for solving the investigated problem, datasets, computational results and comparative analysis of the performance of the existing state-of-the-art algorithms. Additionally, we discuss certain open problems and potential research directions.