發(fā)布時間：2018-04-12 13:25

  本文選題：基值歐式距離 + 改進粒子群算法��； 參考：《機械強度》2017年03期

【摘要】：針對傳統(tǒng)及現(xiàn)有一些多目標優(yōu)化方法在處理實際工程優(yōu)化問題時需要很強的先驗認識、質(zhì)量差、脆弱等不足,提出了一種與基值歐式距離最小為準則的改進粒子群算法與灰色決策相結(jié)合的分步多目標優(yōu)化方法;并將該方法應用于掘進機鏟板參數(shù)多目標優(yōu)化,對優(yōu)化前后鏟板推進煤巖進行了仿真分析和對比,取得了良好的優(yōu)化效果,驗證了該方法的可行性,為工程實際中處理多目標優(yōu)化問題提供了便利與借鑒。
[Abstract]:In view of the shortcomings of traditional and existing multi-objective optimization methods in dealing with practical engineering optimization problems, such as strong prior understanding, poor quality and fragility, etc.In this paper, an improved particle swarm optimization method based on minimum Euclidean distance is proposed, which is combined with grey decision, and the method is applied to the multi-objective optimization of excavator shovel plate parameters.The simulation analysis and comparison of shovel plate propelling coal and rock before and after optimization are carried out, and good optimization results are obtained. The feasibility of this method is verified, which provides convenience and reference for dealing with multi-objective optimization problem in engineering practice.
【作者單位】： 宿州學院機械與電子工程學院;遼寧工程技術(shù)大學機械工程學院;
【基金】：國家自然科學基金項目(51304107) 遼寧省教育廳創(chuàng)新團隊項目(LT2013009) 宿州學院機械設計制造及其自動化專業(yè)帶頭人項目(2014XJZY31)資助~~
【分類號】：TD421.5;TP18

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1 王厚昌;選礦全流程綜合生產(chǎn)指標動態(tài)多目標優(yōu)化方法[D];東北大學;2014年

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本文編號：1739934