A Population Based Approach for ACO

A population based ACO (Ant Colony Optimization) algorithm is proposed where (nearly) all pheromone information corresponds to solutions that are members of the actual population. Advantages of the population based approach are that it seems promising for solving dynamic optimization problems, its f...

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Hauptverfasser:	Guntsch, Michael, Middendorf, Martin
Format:	Buchkapitel
Sprache:	eng
Schlagworte:	Applied sciences Exact sciences and technology Flows in networks. Combinatorial problems Operational research and scientific management Operational research. Management science
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Beschreibung
Zusammenfassung:	A population based ACO (Ant Colony Optimization) algorithm is proposed where (nearly) all pheromone information corresponds to solutions that are members of the actual population. Advantages of the population based approach are that it seems promising for solving dynamic optimization problems, its finite state space and the chances it offers for designing new metaheuristics. We compare the behavior of the new approach to the standard ACO approach for several instances of the TSP and the QAP problem. The results show that the new approach is competitive.
ISSN:	0302-9743 1611-3349
DOI:	10.1007/3-540-46004-7_8