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http://dx.doi.org/10.3745/KIPSTB.2003.10B.3.237

A Study about Additional Reinforcement in Local Updating and Global Updating for Efficient Path Search in Ant Colony System  

Lee, Seung-Gwan (경희대학교 대학원 전자계산공학과)
Chung, Tae-Choong (경희대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartB / v.10B, no.3, 2003 , pp. 237-242 More about this Journal
Abstract
Ant Colony System (ACS) Algorithm is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP). In this paper, we introduce ACS of new method that adds reinforcement value for each edge that visit to Local/Global updating rule. and the performance results under various conditions are conducted, and the comparision between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with tile original ACS in terms of solution quality and computation speed to these problem.
Keywords
Ant System, AS; Ant Colony System, ACS; Global Updating; Local Updating; Reinforcement Learning; Meta Heuristic;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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