Abstract
Abstract In order to reduce the carbon emission and improve the de-carbonization in distribution of vehicle routing problem with simultaneous delivery and pickup (VRPSDP), a two-stage disruption management method based on the changes of customer demand is proposed in this paper. Firstly, a mathematics model of VRPSDP is established to optimize the parameters and the distribution carbon emission cost and time window deviation. Next, several carbon emission equations in VRPSDP are inducted and designed. Considering the strong global searching ability of quantum particle swarm optimization (QPSO) and combing the advantages of superposition and parallelism of quantum computing, a multi-phase QPSO (MQPSO) is proposed to enhance global searching ability. At last, on the basis of Solomon examples, the validity of the proposed model and MQPSO is tested and compared with the classical algorithms at present. The simulation results show that the proposed method can not only achieve the goal of performance but also meet the practical requirements of reducing carbon emissions in VRPSDP.
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