Competitive ant colony optimisation

Authors:
Marcus Randall
Affiliations:
School of Information Technology, Bond University, QLD, Australia
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

Citing 4
Cited 1

A genetic algorithm for the generalised assignment problem

Computers and Operations Research
The ant colony optimization meta-heuristic

New ideas in optimization
HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem

HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem
Ant colony system: a cooperative learning approach to the traveling salesman problem

IEEE Transactions on Evolutionary Computation

Enhancements to extremal optimisation for generalised assignment

ACAL'07 Proceedings of the 3rd Australian conference on Progress in artificial life

Quantified Score

Hi-index	0.00

Visualization

Abstract

The usual assumptions of the ant colony meta-heuristic are that each ant constructs its own complete solution and that it will then operate relatively independently of the rest of the colony (with only loose communications via the pheromone structure). However, a more aggressive approach is to allow some measure of competition amongst the ants. Two ways in which this can be done are to allow ants to take components from other ants or limit the number of ants that can make a particular component assignment. Both methods involve a number of competitions so that the probabilistic best assignment of component to ant can be made. Both forms of competitive ant colony optimisation outperform a standard implementation on the benchmark set of the assignment type problem, generalised assignment.