基于遗传算法的多种约束条件下铣削作业多目标优化

Li-Bao An, Peiqing Yang, Hong Zhang, Ming-Ying Chen
{"title":"基于遗传算法的多种约束条件下铣削作业多目标优化","authors":"Li-Bao An, Peiqing Yang, Hong Zhang, Ming-Ying Chen","doi":"10.2991/ijndc.2014.2.2.5","DOIUrl":null,"url":null,"abstract":"In this paper, the parameter optimization problem for face-milling operations is studied. A multi-objective mathematical model is developed with the purpose to minimize the unit production cost and total machining time while maximize the profit rate. The unwanted material is removed by one finishing pass and at least one roughing passes depending on the total depth of cut. Maximum and minimum allowable cutting speeds, feed rates and depths of cut, as well as tool life, surface roughness, cutting force and cutting power consumption are constraints of the model. Optimal values of objective function and corresponding machining parameters are found by Genetic Algorithms. An example is presented to illustrate the model and solution method.","PeriodicalId":318936,"journal":{"name":"Int. J. Networked Distributed Comput.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Multi-Objective Optimization for Milling Operations using Genetic Algorithms under Various Constraints\",\"authors\":\"Li-Bao An, Peiqing Yang, Hong Zhang, Ming-Ying Chen\",\"doi\":\"10.2991/ijndc.2014.2.2.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the parameter optimization problem for face-milling operations is studied. A multi-objective mathematical model is developed with the purpose to minimize the unit production cost and total machining time while maximize the profit rate. The unwanted material is removed by one finishing pass and at least one roughing passes depending on the total depth of cut. Maximum and minimum allowable cutting speeds, feed rates and depths of cut, as well as tool life, surface roughness, cutting force and cutting power consumption are constraints of the model. Optimal values of objective function and corresponding machining parameters are found by Genetic Algorithms. An example is presented to illustrate the model and solution method.\",\"PeriodicalId\":318936,\"journal\":{\"name\":\"Int. J. Networked Distributed Comput.\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Networked Distributed Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/ijndc.2014.2.2.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Networked Distributed Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ijndc.2014.2.2.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

本文研究了面铣削加工的参数优化问题。建立了以单位生产成本和总加工时间最小、利润率最大化为目标的多目标数学模型。根据切割的总深度,通过一次精加工和至少一次粗加工来去除不需要的材料。最大和最小允许切削速度,进给量和切削深度,以及刀具寿命,表面粗糙度,切削力和切削功耗是模型的约束条件。利用遗传算法求出目标函数的最优值和相应的加工参数。给出了一个算例来说明模型和求解方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Objective Optimization for Milling Operations using Genetic Algorithms under Various Constraints
In this paper, the parameter optimization problem for face-milling operations is studied. A multi-objective mathematical model is developed with the purpose to minimize the unit production cost and total machining time while maximize the profit rate. The unwanted material is removed by one finishing pass and at least one roughing passes depending on the total depth of cut. Maximum and minimum allowable cutting speeds, feed rates and depths of cut, as well as tool life, surface roughness, cutting force and cutting power consumption are constraints of the model. Optimal values of objective function and corresponding machining parameters are found by Genetic Algorithms. An example is presented to illustrate the model and solution method.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信