Korhan KarabulutM. Fatih Tasgetiren2025-10-062012978146731509810.1109/CEC.2012.6252941https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866874921&doi=10.1109%2FCEC.2012.6252941&partnerID=40&md5=9665c256db6ef367d1459f931bd563f1https://gcris.yasar.edu.tr/handle/123456789/10170This paper presents a discrete artificial bee colony algorithm (DABC) for solving the traveling salesman problem with time windows (TSPTW) in order to minimize the total travel cost of a given tour. TSPTW is a difficult optimization problem arising in both scheduling and logistic applications. The proposed DABC algorithm basically relies on the destruction and construction phases of iterated greedy algorithm to generate neighboring food sources in a framework of ABC algorithm. In addition it also relies on a classical 1-opt local search algorithm to further 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 very competitive to or even better than the best performing algorithms from the literature. © 2012 IEEE. © 2012 Elsevier B.V. All rights reserved.EnglishArtificial Bee Colony Algorithm, Heuristic Optimization, Iterated Greedy Algorithm, Swarm Intelligence, Traveling Salesman Problem With Time Windows, Artificial Bee Colony Algorithms, Heuristic Optimization, Iterated Greedy Algorithm, Swarm Intelligence, Time Windows, Artificial Intelligence, Benchmarking, Evolutionary Algorithms, Traveling Salesman ProblemArtificial bee colony algorithms, Heuristic optimization, Iterated greedy algorithm, Swarm Intelligence, Time windows, Artificial intelligence, Benchmarking, Evolutionary algorithms, Traveling salesman problemConference Object