摘要
集装箱装箱问题属于NP（Non-Deterministic Polynomial）问题，为提高集装箱的空间利用率，降低物流配送的成本，合理的装箱方案是必不可少的。针对三维单箱装箱问题，提出一种基于改进遗传算法的人工智能算法，用来实现所建立的优化模型。结合实际装箱问题，分析装箱问题的约束条件，建立数学优化模型，通过将目标函数作为适应度函数和遗传操作中采用排序选择法、部分匹配交叉来实现对传统遗传算法的改进。最后，通过MATLAB编程实现该优化模型的求解，实现了集装箱装载效率的提高。
The container packing problem is a kind of NP（Non-Deterministic Polynomial） problem. In order to improve the space＇s utilization of the container and reduce the cost of logistics and distribution, a reasonable boxing program is essential. An artificial intelligence algorithm based on improved genetic algorithm was proposed to realize the optimization model for Three- dimensional single - box packing problem. Based on the actual packing problem, the mathematical optimization model was established by analyzing the constraint conditions of the packing problem. Through the objective function as a fitness function, the sorting selection method in genetic operation, and partially matched crossover, the improvement of traditional genetic algorithm is realized. Finally through the MATLAB programming, the optimization mode was conducted. As a result, the container loading efficiency is improved.
出处
《工业工程与管理》
CSSCI
北大核心
2018年第1期86-89,共4页
Industrial Engineering and Management
基金
国家自然科学基金资助项目(51108040)
中央高校基本科研业务费专项资金资助项目(310822151022)
