一种改进的量子旋转门遗传算法求解作业车间调度问题

2018 International Conference on Information Systems and Computer Aided Education (ICISCAE) Pub Date : 2018-07-01 DOI:10.1109/ICISCAE.2018.8666865

Ling Li, Guangzhen Cui, X. Lv, Xiaodong Sun, Huaixiao Wang

{"title":"一种改进的量子旋转门遗传算法求解作业车间调度问题","authors":"Ling Li, Guangzhen Cui, X. Lv, Xiaodong Sun, Huaixiao Wang","doi":"10.1109/ICISCAE.2018.8666865","DOIUrl":null,"url":null,"abstract":"In this paper, a hybrid quantum genetic algorithm (QGA) is proposed to solve a new job shop scheduling problem. The improvement of quantum genetic algorithm is as follows: the coding of job shop scheduling problem (JSSP) is analyzed; a new quantum rotation gate is introduced to update quantum chromosome. Finally, the simulation examples show that the new quantum rotation gate improves the traditional genetic algorithm and provides powerful support for the scheduling job shop.","PeriodicalId":129861,"journal":{"name":"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An Improved Quantum Rotation Gate in Genetic Algorithm for Job Shop Scheduling Problem\",\"authors\":\"Ling Li, Guangzhen Cui, X. Lv, Xiaodong Sun, Huaixiao Wang\",\"doi\":\"10.1109/ICISCAE.2018.8666865\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a hybrid quantum genetic algorithm (QGA) is proposed to solve a new job shop scheduling problem. The improvement of quantum genetic algorithm is as follows: the coding of job shop scheduling problem (JSSP) is analyzed; a new quantum rotation gate is introduced to update quantum chromosome. Finally, the simulation examples show that the new quantum rotation gate improves the traditional genetic algorithm and provides powerful support for the scheduling job shop.\",\"PeriodicalId\":129861,\"journal\":{\"name\":\"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCAE.2018.8666865\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE.2018.8666865","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

本文提出了一种混合量子遗传算法(QGA)来解决一个新的作业车间调度问题。量子遗传算法的改进如下:分析了作业车间调度问题(JSSP)的编码;引入一种新的量子旋转门来更新量子染色体。最后，仿真实例表明，新的量子旋转门算法改进了传统的遗传算法，为作业车间调度提供了强有力的支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

An Improved Quantum Rotation Gate in Genetic Algorithm for Job Shop Scheduling Problem

In this paper, a hybrid quantum genetic algorithm (QGA) is proposed to solve a new job shop scheduling problem. The improvement of quantum genetic algorithm is as follows: the coding of job shop scheduling problem (JSSP) is analyzed; a new quantum rotation gate is introduced to update quantum chromosome. Finally, the simulation examples show that the new quantum rotation gate improves the traditional genetic algorithm and provides powerful support for the scheduling job shop.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)

自引率

0.00%

发文量