装配线
遗传算法
编码(内存)
计算机科学
直线(几何图形)
解码方法
算法
体积热力学
卡车
数学优化
数学
工程类
人工智能
机器学习
物理
航空航天工程
机械工程
量子力学
几何学
作者
Yeo Keun Kim,Yeongho Kim,Yong Ju Kim
标识
DOI:10.1080/095372800232478
摘要
A two-sided assembly line balancing problem is typically found in plants producing large-sized high-volume products, e.g. buses and trucks. The features specific to the assembly line are described in this paper, which are associated with those of: (i) two-sided assembly lines; (ii) positional constraints; and (iii) balancing at the operational time. There exists a large amount of literature in the area of line balancing, whereby it has mostly dealt with one-sided assembly lines. A new genetic algorithm is developed to solve the problem, and its applicability and extensibility are discussed. A genetic encoding and decoding scheme, and genetic operators suitable for the problem are devised. This is particularly emphasized using problem-specific information to enhance the performance of the genetic algorithm (GA). The proposed GA has a strength that it is flexible in solving various types of assembly line balancing problems. An experiment is carried out to verify the performance of the GA, and the results are reported.
科研通智能强力驱动
Strongly Powered by AbleSci AI