期刊
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
卷 50, 期 11, 页码 4732-4745出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2018.2861879
关键词
Optimization; Delays; Approximation algorithms; Convergence; Biological cells; Search problems; Memetics; Extreme solutions (ESs); hybrid local search; multiobjective optimization; periodic vehicle routing problem with time windows (PVRPTWs); two-phase strategy
资金
- National Natural Science Foundation of China [61673403, 71601191, U1611262]
- Foundation of Key Laboratory of Machine Intelligence and Advanced Computing of the Ministry of Education [MSC-201606A]
Periodic vehicle routing problem with time windows (PVRPTWs) is an important combinatorial optimization problem that can be applied in different fields. It is essentially a multiobjective optimization problem due to the problem nature. In this paper, a typical multiobjective PVRPTW with five objectives is first defined and new nonsymmetric real-world multiobjective PVRPTW instances are generated. Then, a hybrid multiobjective memetic algorithm is proposed for solving multiobjective PVRPTW. In the proposed algorithm, a two-phase strategy is devised to improve the comprehensive performance in terms of the convergence and diversity. In this strategy, several extreme solutions near an approximate Pareto front (PF) are identified at Phase I, and then the approximate PF is extended at Phase II. The proposed algorithm is extensively tested on both real-world instances and traditional instances. Experiment results show that the proposed algorithm outperforms two representative competitor algorithms on most of the instances. The effectiveness of the two-phase strategy is also confirmed.
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