Multi-Objective Multicast Routing based on Ant Colony Optimization

被引：0
作者：
Pinto, Diego [1 ]
Baran, Benjamin [1 ]
Fabregat, Ramon
机构：
[1] Natl Univ Asuncion, Natl Comp Ctr, Asuncion, Paraguay
来源：
ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT | 2005年 / 131卷
关键词：
Evolutionary; Algorithms; Traffic Engineering; Multicast Routing; Multi objective; Optimization; Pareto Front and Ant Colony Optimization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This work presents a new multiobjective algorithm based on ant colonies which is used in the construction of the multicast tree for data transmission in a computer network The proposed algorithm simultaneously optimizes cost of the multicast tree average delay and maximum end to end delay In this way a set of optimal solutions know as Pareto set is calculated in only one run of the algorithm without a priori restrictions The proposed algorithm was inspired in a Multi objective Ant Colony System (MOACS) Experimental results prove the proposed algorithm outperforms a recently published Multiobjective Multicast Algorithm (MMA) specially designed for solving the multicast routing problem
引用
收藏
页码：363 / 370
页数：8
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