| In recent years,due to the impact of e-commerce,the real economy began to try strategic transformation.And the e-commerce industry with Internet innovation genes is not selfconfident,but also actively integrate with the real economy.So the integration of online and offline marketing channels has become a new trend in the distribution industry.However,they also encounter many management problems in channel integration,including the supply chain configuration which this paper focuses on.Reviewing the existing research on omni-channel supply chain,few studies about online and offline inventory allocation and multi-echelon distribution routing configuration in the omni-channel distribution network have considered multi-echelon,multi-node and multi-agent,which is also a key challenge for enterprises to achieve low logistics cost and high quality of service in supply chain configuration.In order to make up for the blank of the existing research here,and help enterprises better complete the integration of online and offline channels,this paper carries out a series of related studies on the typical multi-echelon distribution network under the omni-channel mode.Firstly,in order to assist enterprises to achieve quantitative resource configuration,this paper extends the existing multi-echelon inventory system model,and constructs an integrated optimal configuration all-in-one model of "inventory-routing" for multi-cycle conventional operation of omni-channel multi-echelon distribution network.Secondly,by introducing the analytical target cascading(ATC)method in multidisciplinary design optimization,the model is decomposed and the distributed integrated optimization configuration model is constructed to solve the problem of cross-agent coordination in reality.Thirdly,because of the characteristics of multi-echelon,multi-node and high dynamic business environment of distribution network,both the difficulty factor and real-time requirement of solving "inventory-routing" problem is high.Therefore,based on the hybrid genetic algorithm and particle swarm optimization algorithm(HGAPSO)in intelligent optimization algorithm,this paper improves and designs two solving strategies for the integrated optimal configuration problem of non-distributed and distributed multi-echelon distribution network.Finally,by two simulation examples,the performance of genetic algorithm(GA),particle swarm optimization(PSO)and HGAPSO are compared,and the key parameters of the algorithm and model are analyzed by single factor control variable method.The results show that the HGAPSO can not only obtain high quality solutions similar to GA,but also benefit from the fast convergence of PSO to reduce the running time.The quality of the solution can be continuously improved by increasing the iteration proportion of the genetic algorithm in the serial HGAPSO in the total iteration and the crossover probability.However,the three key parameters,mutation probability,learning factor and inertia weight,have a non-linear effect on the quality of the solution,which needs to be optimized through parameter in practical application.In terms of management,this paper finds that the multiechelon distribution network under the omni-channel mode is obviously superior to the traditional dual-channel mode in logistics cost.The configurable "inventory-routing" of the whole network endows the flexible distribution capability of the multi-echelon omni-channel distribution network,which can deal with the high inventory cost caused by the high uncertainty of product demand by gathering the online inventory on the upstream in the distribution network,and distribute online inventory downstream to resist the cost of high-line distribution when the uncertainty of product demand is low. |
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