Korhan KarabulutM. Fatih Tasgetiren2025-10-062013978146735905410.1109/CIPLS.2013.6595206https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885008529&doi=10.1109%2FCIPLS.2013.6595206&partnerID=40&md5=402d48554b4598c6b17b4a765c55480bhttps://gcris.yasar.edu.tr/handle/123456789/10075This paper presents a discrete artificial bee colony algorithm (DABC) for solving the team orienteering problem with time windows (TOPTW). The proposed algorithm employs a destruction and construction procedure to generate neighboring food sources in the framework of the DABC algorithm. In addition a variable neighborhood descent (VND) algorithm is developed to enhance the solution quality. The performance of the algorithm was tested on a benchmark set from the literature. Experimental results show that the proposed DABC algorithm is competitive to the best performing algorithms from the literature. Ultimately 11 instances are further improved by the proposed DABC algorithm. © 2013 IEEE. © 2013 Elsevier B.V. All rights reserved.EnglishArtificial Bee Colony Algorithm, Heuristic Optimization, Iterated Greedy Algorithm, Swarm Intelligence, Team Orienteering Problem With Time Windows, Artificial Bee Colony Algorithms, Heuristic Optimization, Iterated Greedy Algorithm, Swarm Intelligence, Time Windows, Artificial Intelligence, Benchmarking, AlgorithmsArtificial bee colony algorithms, Heuristic optimization, Iterated greedy algorithm, Swarm Intelligence, Time windows, Artificial intelligence, Benchmarking, AlgorithmsConference Object