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Optimization of the Sino-Europe Transport Networks Under Uncertain Demand

Qing Nie (), Songyun Liu (), Qiyuan Qian (), Zheyi Tan () and Huiwen Wang
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Qing Nie: School of Management, Shanghai University, Shanghai, P. R. China
Songyun Liu: School of Management, Shanghai University, Shanghai, P. R. China
Qiyuan Qian: School of Management, Shanghai University, Shanghai, P. R. China
Zheyi Tan: School of Management, Shanghai University, Shanghai, P. R. China
Huiwen Wang: School of Management, Shanghai University, Shanghai, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2021, vol. 38, issue 03, 1-29

Abstract: This paper studies a consolidation center selection and cargo transportation optimization problem of the Sino-Europe railway express. It takes account of demand uncertainty and multiple cost factors, such as transportation cost, time cost, waiting cost before consolidation, penalty cost of not full load after distribution, track changing cost, and customs clearance fee. A complicated mixed-integer programming (MIP) model is presented to describe the problem. Then a solution method based on binary particle swarm optimization (BPSO) is designed to solve the model of different scales of cases. Extensive numerical experiments generated from real-world data are conducted to validate the effectiveness of the proposed model. Moreover, we compare the efficiency of the solution method with a commercial solver and a heuristic algorithm based on variable neighborhood search (VNS). Results show that our solution method can optimally solve the problem in small-scale cases and get near-optimal solutions for large-scale problem instances. The proposed mathematical model and the calculation results may provide valuable insights for both business owners and government.

Keywords: Sino-Europe railway express; consolidation centers; mixed-integer programming; binary particle swarm optimization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0217595921400194

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