TY - GEN
T1 - Research on an improved genetic algorithm for logistics distribution path optimization
AU - Sun, Xue
AU - Yang, Chih Kuang
AU - wei, kai-cheng
AU - Wu, Chao-Chin
AU - Chen, Liang-Rui
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Logistics distribution path optimization as an NP-hard problem is one of the important problems in logistics. Many intelligent algorithms are considered to be used to solve such problems. In this paper, an improved genetic algorithm is proposed for solving Travelling Salesman Problem (TSP), a kind of classical logistics distribution path optimization problem. The method uses island model genetic algorithm to formulate rules that are more suitable for TSP, through applying greedy algorithm in the generation of initial population, modifying the selection method and discussing different migration strategies, the computation time of solving the problem is shorten, the calculation efficiency is improved, and the probability of falling into the local optimal solution is reduced. Finally, experiments are conducted to discuss the effectiveness of our method.
AB - Logistics distribution path optimization as an NP-hard problem is one of the important problems in logistics. Many intelligent algorithms are considered to be used to solve such problems. In this paper, an improved genetic algorithm is proposed for solving Travelling Salesman Problem (TSP), a kind of classical logistics distribution path optimization problem. The method uses island model genetic algorithm to formulate rules that are more suitable for TSP, through applying greedy algorithm in the generation of initial population, modifying the selection method and discussing different migration strategies, the computation time of solving the problem is shorten, the calculation efficiency is improved, and the probability of falling into the local optimal solution is reduced. Finally, experiments are conducted to discuss the effectiveness of our method.
UR - http://www.scopus.com/inward/record.url?scp=85066811728&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066811728&partnerID=8YFLogxK
U2 - 10.1145/3321619.3321674
DO - 10.1145/3321619.3321674
M3 - Conference contribution
AN - SCOPUS:85066811728
SN - 9781450366045
T3 - ACM International Conference Proceeding Series
SP - 282
EP - 286
BT - ACM International Conference Proceeding Series
PB - Association for Computing Machinery
T2 - 2018 Asia-Pacific Conference on Intelligent Medical, APCIM 2018 and 7th International Conference on Transportation and Traffic Engineering, ICTTE 2018
Y2 - 21 December 2018 through 23 December 2018
ER -