Abstract
Supply chain service platform (SCSP) plays an indispensable role in omni-fulfillment supply chain network services in the digital economy era. In this context, this paper studies the omni-fulfillment supply chain network design considering cost, service, and resilience tradeoffs. The problem is modeled as a multi-objective mixed integer nonlinear programming (MOMINLP) model based on omni-fulfillment services. To improve the solving efficiency, the model is linearized, and a tailored multi-objective optimization algorithm is developed. The significant advantage of this algorithm is that the multi-loop skipping mechanism is embedded in the Epsilon-constraint method to obtain the Pareto front faster. The effectiveness of the proposed decision-making framework is verified by real-case data. Numerical results show that the proposed algorithm outperforms AUGMECON2 algorithm in terms of problem size and computational time. In the case of order segmentation, the shorter the delivery time of goods, the higher the cost of the supply chain network. Furthermore, implementing capacity redundancy in the central warehouse can mitigate the impact of different disrupting scenarios.
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