A Modified Genetic Algorithm for Distributed Hybrid Flowshop Scheduling Problem

被引：9

作者：

Sun, Xueyan ^{[1
]}

Shen, Weiming ^{[1
]}

Sun, Bingyan ^{[2
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan, Peoples R China

[2] China Univ Petr, Coll Electromech Engn, Qingdao, Peoples R China

来源：

PROCEEDINGS OF THE 2021 IEEE 24TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD) | 2021年

基金：

中国国家自然科学基金;

关键词：

Distributed hybrid flowshop scheduling problem; genetic algorithm; local search; lower bound; SEARCH ALGORITHM;

D O I：

10.1109/CSCWD49262.2021.9437786

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A centralized manufacturing environment is no longer sufficient to meet market demands. A large number of companies extend their production to a distributed environment. Distributed hybrid flowshop scheduling problem (DHFSP) has become a new research topic in recent years. In this paper, a modified genetic algorithm operator is proposed to change the solution structure and a local search method is improved by employing a new lower bound rule. Through experimental comparison, this algorithm has obvious advantages on the effectiveness of searching better solutions, and the new lower bound rule also reduces the running time of local search.

引用

页码：981 / 986

页数：6

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