选择(遗传算法)
遗传算法
相互依存
计算机科学
装配线
光学(聚焦)
直线(几何图形)
资源(消歧)
算法
工业工程
数学优化
工程类
机器学习
物理
政治学
计算机网络
法学
光学
数学
机械工程
几何学
作者
Daria Leiber,Gunther Reinhart
标识
DOI:10.1080/00207543.2020.1845411
摘要
This article presents a novel approach for the automated design of assembly lines that combines the assembly line balancing problem with resource selection and the positioning of the chosen resources into one single optimisation problem. Existing approaches for the automated planning of assembly plants either focus on one planning step or work through different planning steps sequentially. So far, no method exists that sufficiently takes into account the interdependency between the selection and positioning of resources. This article addresses this problem by presenting a bi-level optimisation approach for the automated design of assembly lines. A nested genetic algorithm is used to solve an assembly line balancing problem that includes the selection of production resources while simultaneously considering the layouting options for the chosen resources. Three examples for the evaluation and validation of the algorithm are presented. The presented approach is economically promising as the design of assembly lines requires a lot of expert knowledge and is still mostly done manually.
科研通智能强力驱动
Strongly Powered by AbleSci AI