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Optimization of empty container allocation for inland freight stations considering stochastic demand.

Kang Chen1, Qingyang Lu1, Xu Xin2

  • 1School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning, 116026, PR China.

Ocean & Coastal Management
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Summary

This study introduces a new model for optimizing empty container allocation for shipping companies in the post-COVID-19 era, even with unpredictable demand. The proposed method effectively manages operational costs amidst fluctuating demand.

Keywords:
COVID-19Differential evolutionEmpty container allocationEmpty container managementStochastic demand

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Area of Science:

  • Logistics and Supply Chain Management
  • Operations Research
  • Maritime Economics

Background:

  • The post-COVID-19 epidemic era (PCEE) presents significant uncertainty in empty container supply, impacting liner companies.
  • Accurate allocation of owned and leased empty containers to inland freight stations is crucial but challenging due to unpredictable demand and inflexible relocation.

Purpose of the Study:

  • To develop a model for optimizing empty container allocation without prior knowledge of demand probability distributions.
  • To jointly optimize the quantities of self-owned and leased empty containers for each inland freight station.

Main Methods:

  • A novel model for empty container allocation is proposed.
  • A largest-debt-first policy is employed to simplify the allocation model.
  • A differential evolutionary (DE) algorithm is utilized to solve the simplified model and compared with traditional methods.

Main Results:

  • The proposed largest-debt-first policy demonstrates superior cost control in high demand fluctuation scenarios compared to traditional methods.
  • The differential evolutionary (DE) algorithm shows effectiveness in exploring optimal solutions for the allocation model.
  • Experimental results validate the model's utility in managing operational and management costs.

Conclusions:

  • The developed theory and method enable carriers to establish optimal regional empty container stock levels.
  • The approach effectively determines the optimal quantities of self-owned and leased empty containers for allocation.
  • This contributes to improved efficiency and cost-effectiveness in empty container management for liner companies.