文件名称:Ga
- 所属分类：
- JSP源码/Java
- 资源属性：
- [Java] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 1kb
- 下载次数：
- 0次
- 提 供 者：
- gardeni*******
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
GA_Traffic
The Traveling Salesman Problem (TSP) is maybe the archetypical problem
in combinatorial optimization. This problem and its generalizations, vehicle
routing problems, have been studied for more than thirty years two entire
monographs are devoted to the subject [34, 26]. Since the TSP is NP-hard,
polynomial-time approximation algorithms are usually studied. However,
usually the approaches to the study of vehicle routing problems adopt an
offline point of view: the input is entirely known beforehand. In many
applications, this is actually not the case since the instance becomes known
in an online fashion, time after time. Even determining when the instance
is completely given could be impossible. The need for an online model then
arises naturally.-GA_Traffic
The Traveling Salesman Problem (TSP) is maybe the archetypical problem
in combinatorial optimization. This problem and its generalizations, vehicle
routing problems, have been studied for more than thirty years two entire
monographs are devoted to the subject [34, 26]. Since the TSP is NP-hard,
polynomial-time approximation algorithms are usually studied. However,
usually the approaches to the study of vehicle routing problems adopt an
offline point of view: the input is entirely known beforehand. In many
applications, this is actually not the case since the instance becomes known
in an online fashion, time after time. Even determining when the instance
is completely given could be impossible. The need for an online model then
arises naturally.
The Traveling Salesman Problem (TSP) is maybe the archetypical problem
in combinatorial optimization. This problem and its generalizations, vehicle
routing problems, have been studied for more than thirty years two entire
monographs are devoted to the subject [34, 26]. Since the TSP is NP-hard,
polynomial-time approximation algorithms are usually studied. However,
usually the approaches to the study of vehicle routing problems adopt an
offline point of view: the input is entirely known beforehand. In many
applications, this is actually not the case since the instance becomes known
in an online fashion, time after time. Even determining when the instance
is completely given could be impossible. The need for an online model then
arises naturally.-GA_Traffic
The Traveling Salesman Problem (TSP) is maybe the archetypical problem
in combinatorial optimization. This problem and its generalizations, vehicle
routing problems, have been studied for more than thirty years two entire
monographs are devoted to the subject [34, 26]. Since the TSP is NP-hard,
polynomial-time approximation algorithms are usually studied. However,
usually the approaches to the study of vehicle routing problems adopt an
offline point of view: the input is entirely known beforehand. In many
applications, this is actually not the case since the instance becomes known
in an online fashion, time after time. Even determining when the instance
is completely given could be impossible. The need for an online model then
arises naturally.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
Ga.java