首页 | 官方网站   微博 | 高级检索  
     

基于组件式蚁群算法的车辆路径问题研究
引用本文:温蕴.基于组件式蚁群算法的车辆路径问题研究[J].微电子学与计算机,2008,25(6).
作者姓名:温蕴
作者单位:浙江丽水广播电视大学,理工教研室,浙江,丽水,323000
摘    要:现有方法仅从蚁群算法的基本结构出发设计软件,缺少软件设计模型的有效指导,很难用来求解不同种类的优化问题.鉴于此,应用组件软件设计方法,提出了一种组件武蚁群算法.该方法力求在结构上直接反映蚁群的本质思想和关键概念;最大程度降低与问题的相关性;强调以接口为中心的设计理念.大量车辆路径问题的验证结果表明,组件式蚁群算法性能优良,能够有效地求解车辆路径问题.该方法易于理解和使用,具有很强的可重用性和可扩展性,为求解各类优化问题提供了很好的起点和可持续发展的框架.

关 键 词:车辆路径问题  组件式蚁群算法  组件软件框架  可重用性  可扩展性

Component-Based Ant Colony Algorithm for Solving Vehicle Routing Problems
WEN Yun.Component-Based Ant Colony Algorithm for Solving Vehicle Routing Problems[J].Microelectronics & Computer,2008,25(6).
Authors:WEN Yun
Abstract:Existing ant colony algorithm(ACA)software was designed only based on its basic structure.Due to lack the guidance of software design model,it is very difficult to design some practicable ACA software for solving different opti- mization problems.For this purpose,it presents a component-based ant colony agorithm(CACA)by applying the compo- nent-based software engineering thoughtway.This CACA emphasizes the direct correspondence of ACA concepts with its software architecture,the minimal coupling with specific problem structure and the interface-centered design.The experi- ment results of many vehicle routing problems(VRP)suggest that the CACA is feasible and valid for VRP.This proposed approach is very easy to understand and employ,it has a very robust reusage and expansibility;it indeed provides a good start point and a framework that can continually improve for solving different optimization problems.
Keywords:vehicle routing problem  component-based ant colony algorithm  component-based framework  reusage  expansibility
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号