Quick search
Go!

ON THE ROBUSTNESS OF ANT COLONY OPTIMIZATION


GLORIA CERASELA CRIŞAN
“Vasile Alecsandri" University of Bacău, Faculty of Sciences, Department of Mathe-matics, Informatics and Educational Sciences, Calea Mărăşeşti 157, Bacău 600115, Romania, e-mail: ceraselacrisan@ub.ro

Issue:

SSRSMI, Number 1, Volume XXIII

Section:

Volume 23, Number 1

Abstract:

The real life faces many situations when people have to handle inconsistent data (i.e. contradictory facts, opposite opinions, etc.), managing them using personal and social experience and beliefs. Generally speaking, social life forms successfully and gracefully treat these conflicting cases – for example, by identifying the false facts and dropping them. In Computer Science and Information Technology, the problem of error identification and correction is a central one, approached in Code Theory, Software Engineering, Databases, Computer Architecture, etc.

This paper studies the behavior of a multi-agent software application when some of the agents have correct information about the solved problem, but the others do not. The well-known Traveling Salesman Problem (TSP) is solved using a biologically-inspired algorithm that models the way real ants manage to find the shortest path from nest to food source. The results are encouraging, showing that the artificial ants manifest the same robustness as real ants.

Keywords:

Big data, Information quality, Inconsistency, Ant algorithms, Combinatorial Optimization.

Code [ID]:

SSRSMI201323V23S01A0003 [0003820]

Full paper:

Download pdf


Copyright (c) 1995-2007 University of Bacu