基于布谷鸟算法的压缩机装配调度项目优化方法  

Compressor Assembly Project Scheduling OptimizationMethod Based on Cuckoo Algorithm

作　　者：曹圣武 陈再良[1] CAO Shengwu;CHEN Zailiang(School of Mechanical and Electrical Engineering,Soochow University,Suzhou 215000,China)

机构地区：[1]苏州大学机电工程学院,江苏苏州215000

出　　处：《机械制造与自动化》2020年第4期84-87,共4页Machine Building & Automation

基　　金：国家自然科学基金(51475313);江苏省科技厅资助项目(BY2016043-02,BA2014004)。

摘　　要：针对制造型企业生产项目调度优化,提出一种基于自适应布谷鸟算法的调度策略。该策略采用全局搜索能力强的布谷鸟算法为框架模型,以任务调度顺序优先级编码,对影响算法性能的重要参数——步长因子设定动态自适应策略,提升算法的运算性能和全局收敛速度。以跨国S公司大型空气压缩机装配项目为例进行调度优化,结果表明该调度方案拥有更短的工期和平衡的资源利用率。此外,通过自动生成的人力配置甘特图,项目经理能够动态调整人员配置以减少人力资源的浪费。For the optimization of production project scheduling in manufacturing enterprises,a scheduling strategy based on adaptive cuckoo algorithm is proposed.In the strategy,the cuckoo algorithm with strong global search ability is adopted as framework model.The priority is given to task scheduling order,and the important parameter step factor affecting the performance of the algorithm is set for the dynamic adaptive strategy which is used to improve the computing performance and global convergence speed of the algorithm.This paper takes the large-scale air compressor assembly project of multinational company as an example.The results show that the scheduling scheme can be used to shorten the construction period and balance the resource utilization.In addition,with the manpower configuration Gantt chart automatically generated,the project manager can dynamically adjust staff,thus reducing the waste of human resources.

关 键 词：生产项目调度 布谷鸟算法 自适应步长 最小化工期 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置]