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Optimization of multistage timeliness transit consolidation problem using adaptive-weighted genetic algorithm.

Bowen Lv1, Bin Yang1, Ek Peng Chew2

  • 1Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, China.

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|June 26, 2023
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Summary

This study introduces a new method for timely cargo consolidation in international shipping, especially for small, multi-batch shipments. The proposed algorithm optimizes logistics networks, improving efficiency and container utilization during global disruptions.

Keywords:
Coupling of multiple ODsImproved genetic algorithmThe COVID-19Timeliness transit consolidationTonnage utilization

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Area of Science:

  • Logistics and Supply Chain Management
  • Operations Research
  • Transportation Science

Background:

  • International cargo consolidation faces challenges with small, multi-batch shipments, leading to delays and underutilized container capacity.
  • The COVID-19 pandemic has amplified the need for timely and efficient international multimodal transport.
  • Existing logistics networks struggle to manage coupled multiple origins and destinations (ODs) effectively.

Purpose of the Study:

  • To define and address the multistage timeliness transit consolidation problem for small, multi-batch international cargo.
  • To enhance connectivity between logistics operations and maximize container capacity utilization.
  • To develop a flexible and efficient algorithm for optimizing international multimodal transport networks.

Main Methods:

  • Defined a multistage timeliness transit consolidation problem to decouple multiple ODs.
  • Proposed a two-stage adaptive-weighted genetic algorithm focusing on Pareto front space and population diversity.
  • Conducted computational experiments to analyze parameter correlations and algorithm performance.

Main Results:

  • Identified regular trends in parameter correlations, indicating that appropriate settings yield better results.
  • Confirmed the significant influence of the pandemic on the market share of different transportation modes.
  • Demonstrated the feasibility and effectiveness of the proposed method through comparisons with other approaches.

Conclusions:

  • The developed algorithm effectively addresses the challenges of timely cargo consolidation for small, multi-batch shipments.
  • Optimized logistics networks lead to increased connectivity and improved container utilization.
  • The research provides valuable insights into optimizing international transport strategies, particularly in response to global events like pandemics.