Scholarlink

<p>In this paper, a fast and precise adjustment algorithm for the transport loading plan of port logistics transport services to ensure on-time arrival has been introduced. The algorithm resolves issues associated with ensuring reliable and efficient transport loading plans that result in reduced rehandling of containers and optimize transport scheduling. The algorithm utilized genetic algorithm solutions to provide efficient adjustments to transport loading plans to ensure satisfaction of on-time delivery requirements. The results of experiments conducted to test the performance of these methods unveiled promising results of up to 99.2% effectiveness in achieving on-time delivery performance, irrespective of transport delays associated with traditional systems. The algorithm effectively reduced transport rehandling of containers associated with transport delays in port logistics systems. The algorithm signifies promising results in improving joint optimization issues associated with genetic algorithm solutions to improve transport delay efficiency in integrated logistics systems. The algorithm signifies promising results in improving transport delay issues associated with joint optimization systems in improving transport systems associated with congested logistics systems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fast and accurate adjustment method for loading plan based on on-time arrival constraints of port logistics transportation

  • 期刊论文

  • 发表日期：

    2026年3月30日

查看全文
  • Zhaomin Zhang,
  • Shiguan Liao

摘要

In this paper, a fast and precise adjustment algorithm for the transport loading plan of port logistics transport services to ensure on-time arrival has been introduced. The algorithm resolves issues associated with ensuring reliable and efficient transport loading plans that result in reduced rehandling of containers and optimize transport scheduling. The algorithm utilized genetic algorithm solutions to provide efficient adjustments to transport loading plans to ensure satisfaction of on-time delivery requirements. The results of experiments conducted to test the performance of these methods unveiled promising results of up to 99.2% effectiveness in achieving on-time delivery performance, irrespective of transport delays associated with traditional systems. The algorithm effectively reduced transport rehandling of containers associated with transport delays in port logistics systems. The algorithm signifies promising results in improving joint optimization issues associated with genetic algorithm solutions to improve transport delay efficiency in integrated logistics systems. The algorithm signifies promising results in improving transport delay issues associated with joint optimization systems in improving transport systems associated with congested logistics systems.