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GORTS: genetic algorithm based on one-by-one revision of two sides for dynamic travelling salesman problemsXu, Xiaolong; Yuan, Hao; Matthew, Peter; Ray, Jeffrey; Bagdasar, Ovidiu; Trovati, Marcello; University of Derby; Nanjing University of Posts and Telecommunications, Nanjing, China; Edge Hill University, Ormskirk, UK (Springer, 2019-09-21)The dynamic travelling salesman problem (DTSP) is a natural extension of the standard travelling salesman problem, and it has attracted significant interest in recent years due to is practical applications. In this article, we propose an efficient solution for DTSP, based on a genetic algorithm (GA), and on the one-by-one revision of two sides (GORTS). More specifically, GORTS combines the global search ability of GA with the fast convergence feature of the method of one-by-one revision of two sides, in order to find the optimal solution in a short time. An experimental platform was designed to evaluate the performance of GORTS with TSPLIB. The experimental results show that the efficiency of GORTS compares favourably against other popular heuristic algorithms for DTSP. In particular, a prototype logistics system based on GORTS for a supermarket with an online map was designed and implemented. It was shown that this can provide optimised goods distribution routes for delivery staff, while considering real-time traffic information.