TY - GEN
T1 - A co-evolution coral reefs optimization approach for multi-objective vehicle routing problem with time windows
AU - Lin, Chang Sheng
AU - Chiang, Ming Chao
AU - Yang, Chu Sing
N1 - Funding Information:
ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their valuable comments and suggestions on the paper. This work was supported in part by the Ministry of Science and Technology of Taiwan, R.O.C., under Contracts MOST107-2221-E-110-021 and MOST108-2221-E-110-028.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - The vehicle routing problem is a critical research issue in logistics because the strategies used may strongly impact its performance. A good strategy would allow the management to make a good decision to enhance the performance of logistics. In practice, we have to consider two or more factors in solving the vehicle routing problem at the same time. An effective hybrid search algorithm for the vehicle routing problem with time windows is presented in this study, which takes into account at the same time the number of vehicles and the total distance for vehicles based on a novel metaheuristic algorithm named coral reefs optimization algorithm with substrate layers (CRO-SL). The experimental results show that the proposed algorithm outperforms all the other state-of-the-art algorithms compared in this paper.
AB - The vehicle routing problem is a critical research issue in logistics because the strategies used may strongly impact its performance. A good strategy would allow the management to make a good decision to enhance the performance of logistics. In practice, we have to consider two or more factors in solving the vehicle routing problem at the same time. An effective hybrid search algorithm for the vehicle routing problem with time windows is presented in this study, which takes into account at the same time the number of vehicles and the total distance for vehicles based on a novel metaheuristic algorithm named coral reefs optimization algorithm with substrate layers (CRO-SL). The experimental results show that the proposed algorithm outperforms all the other state-of-the-art algorithms compared in this paper.
UR - http://www.scopus.com/inward/record.url?scp=85076718630&partnerID=8YFLogxK
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U2 - 10.1109/SMC.2019.8914020
DO - 10.1109/SMC.2019.8914020
M3 - Conference contribution
AN - SCOPUS:85076718630
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 2001
EP - 2006
BT - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
Y2 - 6 October 2019 through 9 October 2019
ER -