TY - JOUR
T1 - GORTS: genetic algorithm based on one-by-one revision of two sides for dynamic travelling salesman problems
AU - Xu, Xiaolong
AU - Yuan, Hao
AU - MATTHEW, PETER
AU - RAY, JEFFREY
AU - Bagdasar, Ovidiu
AU - TROVATI, MARCELLO
N1 - Funding Information:
This work was jointly sponsored by the National Natural Science Foundation of China under Grants 61472192 and 91646116, the Scientific and Technological Support Project (Society) of Jiangsu Province under Grant BE2016776, the Talent Project in Six Fields of Jiangsu Province under Grant 2015-JNHB-012, the “333” Scientific Research program of Jiangsu Province under Grant BRA2017228, and the Jiangsu Key Laboratory of Big Data Security and Intelligent Processing at NJUPT.
Funding Information:
This work was jointly sponsored by the National Natural Science Foundation of China under Grants 61472192 and 91646116, the Scientific and Technological Support Project (Society) of Jiangsu Province under Grant BE2016776, the Talent Project in Six Fields of Jiangsu Province under Grant 2015-JNHB-012, the ?333? Scientific Research program of Jiangsu Province under Grant BRA2017228, and the Jiangsu Key Laboratory of Big Data Security and Intelligent Processing at NJUPT.
Publisher Copyright:
© 2019, The Author(s).
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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.
AB - 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.
KW - DTSP
KW - Path optimisation
KW - One-by-one revision of two slides
KW - Genetic algorithm
UR - http://www.scopus.com/inward/record.url?scp=85074051410&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074051410&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/033799ed-185c-348f-81be-3b617bcb6ac9/
U2 - 10.1007/s00500-019-04335-2
DO - 10.1007/s00500-019-04335-2
M3 - Article (journal)
SN - 1432-7643
VL - 24
SP - 7197
EP - 7210
JO - Soft Computing
JF - Soft Computing
IS - 10
ER -
