Modeling and simulation analysis of optimal layout scheme of aviation logistics park based on genetic algorithm

Jianxin Chen
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Abstract

As an important component of modern logistics industry, aviation logistics parks address the problems of unreasonable layout and low efficiency in traditional planning and construction methods. The study first constructed a grid model for optimizing the layout of functional areas in the aviation logistics park, and selected the layout scheme with the highest comprehensive correlation as the optimal planning. At the same time, three important model parameters were determined: prediction of cargo throughput, size of functional areas in the park, and comprehensive correlation values between functional areas. Subsequently, in response to the optimization problem of functional area layout in aviation logistics parks, a cosine adaptive genetic algorithm based on adaptive reversal operation was introduced to solve the model. According to the findings, the research mention algorithm has an average utilization rate of up to 69.64% in the international freight zone, which is a 12.38% improvement over the conventional genetic algorithm. Additionally, it has an average domestic cargo area utilization rate of 67.93%, 11.24% greater than the genetic algorithm. This demonstrated that the functional area layout scheme of the aviation logistics park produced by examining the suggested algorithm is extremely viable and offers new ideas and techniques for the planning and designing of aviation logistics parks.

基于遗传算法的航空物流园区优化布局方案建模与仿真分析
作为现代物流业的重要组成部分,航空物流园区解决了传统规划建设方式中存在的布局不合理、效率低等问题。研究首先构建了航空物流园区功能区布局优化的网格模型,选取综合相关性最高的布局方案作为最优规划。同时,确定了三个重要的模型参数:货物吞吐量预测值、园区功能区规模和功能区之间的综合关联值。随后,针对航空物流园区功能区布局的优化问题,引入了基于自适应逆运算的余弦自适应遗传算法来求解模型。研究结果表明,该算法在国际货运区的平均利用率高达 69.64%,比传统遗传算法提高了 12.38%。此外,它的国内货运区平均利用率为 67.93%,比遗传算法高出 11.24%。这表明,通过研究建议算法得出的航空物流园区功能区布局方案极具可行性,为航空物流园区的规划设计提供了新的思路和技术。
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