In configuration optimization of truss with mixed variables , mixed coded strategies are proposed which are binary and floating coding , integer and floating coding 對(duì)于混合變量的析架形狀優(yōu)化問題,本文提出了混合編碼策略,即二進(jìn)制和實(shí)數(shù)混合編碼、整數(shù)和實(shí)數(shù)混合編碼。
2 . analyze two kinds of coding strategy and give some feathers of the coding method which can be used to analyze the search ability of ga operators . 3 編碼策略是設(shè)計(jì)遺傳算法的一個(gè)重要步驟,編碼也成為遺傳算法應(yīng)用中的首要問題,因而建立完善的編碼方面的理論指導(dǎo)是必要的。
In our work , we use an object oriented feature - based coding strategy in the following two applications : the simulation for the human ' s letters identified experiment and the data analysis of the seawater ' s quality 我們應(yīng)用面向?qū)ο蟮奶卣骶幋a成功地將art應(yīng)用于人的英文26個(gè)字母認(rèn)知識(shí)別實(shí)驗(yàn)的仿真與海域水質(zhì)數(shù)據(jù)的分析中。
During solving the problem , presents a different code strategy from other general ones , discusses some important factors that influence the algorithm characteristics and gets the ranges of the parameters b y experiments 最后,將改進(jìn)的免疫遺傳算法應(yīng)用于tsp這一典型的組合優(yōu)化問題,提出與以往不同的編碼方案,通過(guò)實(shí)驗(yàn),確定了算法中參數(shù)的取值范圍。
The research contents can be outlined as bellow : ( 1 ) it has analyzed the basic principle and characteristics of ga and investigated the ga coding strategy and its operators in detail 論文主要研究工作和取得成果如下: 1 .研究遺傳算法的基本原理及其優(yōu)缺點(diǎn),了解其廣泛的應(yīng)用領(lǐng)域,特別是在電力系統(tǒng)的應(yīng)用情況,并且詳細(xì)地分析了遺傳算法的編碼策略與操作算子。
The mathematical models of topology and size optimization of trusses are given firstly , and then a co - evolution mechanism for optimization of both models , including coding strategies and the construction of fitness functions , is described 先給出桁架拓?fù)浜统叽鐑?yōu)化的數(shù)學(xué)模型,再對(duì)協(xié)同演化的機(jī)理進(jìn)行說(shuō)明,給出算法在桁架問題上實(shí)現(xiàn)的編碼策略、適應(yīng)值函數(shù)構(gòu)造等方法。
As core searching algorithm , genetic algorithm is applied to generate software structural test case . to achieve higher performance , such issues as coding strategy , evaluation function construction and instrumentation are discussed in detail . in particular , much emphasis is put on how to improve the genetic algorithm operator which has a significant influence on the algorithm efficiency 該技術(shù)采用遺傳算法作為核心搜索算法來(lái)生成軟件結(jié)構(gòu)測(cè)試用例,其中討論了編碼策略、評(píng)價(jià)函數(shù)構(gòu)造及插裝等問題的解決方案,并重點(diǎn)說(shuō)明了如何對(duì)遺傳算子進(jìn)行改進(jìn),使算法在解決本問題時(shí)更加有效。
Second , by combining theories of strength of laminate with ga , a new gradient free optimization method with new code strategy is discussed . the representation itself does not change the nature of the problem , but effects the searching efficiency of the algorithm . so the representation of the parameters to be optimized is a very important factor and the new code strategy is also easy used with crossover operator and variation operator in ga applications 其次,本文根據(jù)層合板優(yōu)化設(shè)計(jì)的具體問題提出了一種符號(hào)編碼方式,雖然優(yōu)化參數(shù)的基因編碼表達(dá)方式并不能改變優(yōu)化問題的本質(zhì),但是不同的編碼表達(dá)方式對(duì)于遺傳算法搜索的效率和最終的優(yōu)化結(jié)果有著重要的影響,因此優(yōu)化參數(shù)的基因編碼表達(dá)是遺傳算法應(yīng)用于工程問題中非常關(guān)鍵的一步。