An extended ant colony algorithm and its convergence analysis

被引：5

作者：

Sebastiani, G ^{[1
]}

Torrisi, GL ^{[1
]}

机构：

[1] CNR, Ist Applicaz Calcolo M Picone, I-00161 Rome, Italy

来源：

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY | 2005年 / 7卷 / 02期

关键词：

ant colony; convergence analysis; simulation; stochastic optimization;

D O I：

10.1007/s11009-005-1485-z

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this work, we propose a stochastic algorithm for solving NP - hard combinatorial optimization problems. The procedure is formulated within the Ant Colony Optimization (ACO) framework, and extends the so-called Graph-based Ant System with time-dependent evaporation factor, (GBAS/tdev) studied in Gutjahr ( 2002). In particular, we consider an ACO search procedure which also takes into account the objective function value. We provide a rigorous theoretical study on the convergence of the proposed algorithm. Further, for a toy example, we compare by simulation the rate of convergence of the proposed algorithm with those from the Random Search (RS) and from the corresponding procedure in Gutjahr ( 2002).

引用

页码：249 / 263

页数：15

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