Abstract
Considering the high demand volatility, short shelf life and sales period of perishable goods, it is necessary to analyze the application of multi-period distribution in closed-loop supply chain network (CLSC) system. At the same time, considering the environmental pollution caused by improper handling, sales and reputation loss caused by untimely delivery, uncertain demand and recovery of perishable goods in different periods, a mixed integer programming (MIP) model and its corresponding robust optimization model of multi-period and multi-objective CLSC network for perishable goods are established aiming at the minimum environmental impact, the minimum economic cost and the maximum on-time delivery rate. The validity and feasibility of robust optimization model were verified by a hybrid heuristic algorithm with a case study of cross-region CLSC network covering cities of Shanghai, Suzhou, Wuxi, Changzhou, Jiaxing and Huzhou in Eastern China. The numerical results show that, compared with the single period system, the multi-period system has the advantages of good dynamic performance and low system cost, and the multi-objective optimization is better than the single-objective optimization on the whole; meanwhile, the importance of uncertain factors in the decision-making of robust optimization model is verified. This research provides important managerial insights about network design and optimal operation of CLSC for perishable goods under uncertainty.
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Sun, Z., Guo, J., Liang, C., Gen, M. (2020). Robust Optimizing a Multi-period Multi-objective Closed-Loop Supply Chain Network for Perishable Goods Using Hybrid Heuristic Algorithm Under Uncertainty. In: Chan, F.K.S., Chan, H.K., Zhang, T., Xu, M. (eds) Proceedings of the 2020 International Conference on Resource Sustainability: Sustainable Urbanisation in the BRI Era (icRS Urbanisation 2020). icRSUrbanisation 2020. Environmental Science and Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-9605-6_2
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DOI: https://doi.org/10.1007/978-981-15-9605-6_2
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