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Intelligent Selection Algorithm of Optimal Logistics Distribution Path Based on Supply Chain Technology.

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  • 1Zhejiang Industry & Trade Vocational College, Wenzhou 325003, Zhengjiang, China.

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This study introduces an intelligent logistics distribution system for steel enterprises, optimizing vehicle scheduling and delivery routes. It enhances efficiency and reduces costs through a comprehensive service platform and advanced algorithms.

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Area of Science:

  • Operations Research
  • Supply Chain Management
  • Information Technology

Background:

  • Logistics distribution intelligence is a critical research area, with persistent challenges in vehicle allocation, route optimization, and cost reduction for efficiency.
  • Steel enterprises face significant operational inefficiencies, inadequate resource planning, and suboptimal management in their logistics supply chains.
  • The integration of logistics supply chain services and the development of comprehensive service platforms are pressing needs within the industry.

Purpose of the Study:

  • To analyze and reengineer core warehousing and distribution processes within steel enterprises.
  • To establish an integrated logistics supply chain model for steel companies.
  • To develop and implement an intelligent system for optimizing logistics distribution path planning and vehicle scheduling.

Main Methods:

  • Qualitative analysis of warehousing and distribution modules.
  • Implementation of business process reengineering principles.
  • Development of a comprehensive service platform utilizing Radio Frequency Identification (RFID) technology.
  • Application of multi-objective optimization methods, including a genetic algorithm, for distribution path planning.
  • Design and implementation of a logistics vehicle scheduling management system.

Main Results:

  • A conceptual framework for an integrated logistics supply chain in steel enterprises was established.
  • A functional logistics vehicle scheduling management system was designed and implemented.
  • The study demonstrated the effectiveness of a multi-objective genetic algorithm in solving small-scale distribution route optimization and vehicle scheduling problems.
  • Radio Frequency Identification (RFID) technology was integrated to realize the comprehensive service platform concept.

Conclusions:

  • The proposed integrated service platform and optimized distribution strategies significantly improve the efficiency and cost-effectiveness of logistics operations in steel enterprises.
  • The developed system and algorithms provide a practical solution for addressing complex vehicle scheduling and route optimization challenges in logistics distribution.
  • This research contributes to the advancement of intelligent logistics systems, particularly for industries with complex supply chain requirements like the steel sector.