一種蟻群優(yōu)化算法的應(yīng)用初探

信息計(jì)算科學(xué)論文編號(hào):XXLW010 論文字?jǐn)?shù):7808,頁(yè)數(shù):16

目  錄
摘要 i
Abstract ii
目錄 III
一、引言 1
二、 蟻群算法的原理及步驟 3
2.1 蟻群優(yōu)化原理及算法描述 3
2.1.1 蟻群的自組織行為 3
2.1.2 蟻群優(yōu)化算法描述 5
2.2蟻群搜尋理論和算法介紹 6
2．2.1 蟻群搜尋理論 6
2．2.2 基于搜尋理論的算法描述 7
三、 應(yīng)用初探-勞動(dòng)力就業(yè)指標(biāo)分析模型 8
3.1勞動(dòng)力就業(yè)概述 8
3.2模型建立 8
3.3模型求解及結(jié)果分析 9
四、 結(jié)束語(yǔ) 13
五、 致謝 14
六、參考文獻(xiàn) 15

摘要

 優(yōu)化技術(shù)是一種以數(shù)學(xué)為基礎(chǔ)，用于求解各種工程問(wèn)題優(yōu)化解的應(yīng)用技術(shù)。隨著數(shù)學(xué)科研領(lǐng)域的迅速發(fā)展，優(yōu)化問(wèn)題成了一個(gè)熱門(mén)研究問(wèn)題。而由于其算法的復(fù)雜性和計(jì)算量的逐漸增加，越來(lái)越多的革新算法不斷產(chǎn)生，蟻群算法就是其中一種有效工具。本文基于這個(gè)觀點(diǎn)，引入了一種新型的優(yōu)化算法—蟻群算法來(lái)加以學(xué)習(xí)整理。在此基礎(chǔ)上，將該方法針對(duì)就業(yè)問(wèn)題進(jìn)行初步應(yīng)用。本文先介紹了蟻群優(yōu)化算法的定義、原理及多種算法，在文獻(xiàn)[4]中有詳細(xì)介紹它的原理和算法。再對(duì)諸多算法加以對(duì)比分析，并引出了搜尋理論，最后選用一種最適合的算法，針對(duì)杭州市勞動(dòng)力就業(yè)搜尋問(wèn)題，對(duì)算法模型進(jìn)行分析。在對(duì)搜尋時(shí)間和搜尋成本這兩個(gè)指標(biāo)上加以研究對(duì)比得出結(jié)果，給出結(jié)果的優(yōu)劣性，最后得出結(jié)論：這種蟻群算法可以縮短成功就業(yè)搜尋時(shí)間，降低搜尋成本，能充分體現(xiàn)優(yōu)化的效果。

關(guān)鍵詞：優(yōu)化問(wèn)題  蟻群算法  搜尋理論  勞動(dòng)力就業(yè)

A preliminary application for
an optimized algorithm of the ant colony theory

Abstract

 Optimization technology is a mathematical basis for solving various problems of optimization of the application of technology. With the rapid development of mathematical field of scientific research,the optimization has become a hot research issues. And because of the complexity of its algorithm and gradually increasing of the amount of computation, more and more innovative algorithms are constantly generated, the ant algorithm is one of the effective tools.This article stems from this viewpoint, introduced one kind of new optimized algorithm -ant group algorithm to come to study and the preliminary application. On this basis,we will use this method on the point of unemployment to do the initial application.We first introduced the definition 、principles 、and algorithms of the ant colony optimization in this article,there are written in detail about its principles and algorithms in the literature [4]，then we do a lot of comparative analysis, and lead to the search theory，at last we choose a most suitable method and use the example of the employment search in HangZhou to verify the analysis. In the research of its searching time and searthing cost of these two indicators ,we compared the two resuits and analyse the goods and bads .Finally we find that it has shorrten the time for a successful job search and  reduced the search for lower costs by using this ant colony algorithm.And finally reflects the optimization of the results.
 
Keywords: Optimization，Ant algorithm，Search theory，Employment