On the harmonious mating strategy through tabu search
Information Sciences: an International Journal - Special issue: Evolutionary computation
DiGA: Population diversity handling genetic algorithm for QoS-aware web services selection
Computer Communications
Viewing the problem from different angles: a new diversity measure based on angular distances
Journal of Artificial Evolution and Applications
Efficient population diversity handling genetic algorithm for qos-aware web services selection
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
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Abstract: In order to attain the global optimum without getting stuck at a local optimum, an appropriate diversity of the structures in the population needs to be maintained. I propose a new genetic algorithm called DCGA (Diversity Control-oriented Genetic Algorithm) to attain this goal. In DCGA, the structures of the population for the next generation are selected from the merged population of the parents and their offspring based on a selection probability, which is calculated using the Hamming distance between the candidate structure and the structure with the best fitness value. Within the range of my experiments, the performance of DCGA is remarkably superior to that of a simple genetic algorithm, and DCGA seems to be a promising competitor to previously-proposed algorithms.