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A Population based Approach for ACO

A Population based Approach for ACO

Published: 2002
Herausgeber: S. Cagnoni et al.
Buchtitel: Applications of Evolutionary Computing - Evo Workshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Ausgabe: 2279
Reihe: LNCS
Seiten: 72-81
Verlag: Springer

Referierte Veröffentlichung


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.


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