Abstract
To maximize user satisfaction during composition of web services, a genetic algorithm with population diversity handling is presented for Quality of Service(QoS)-aware web services selection. In this algorithm, the fitness function, the selection mechanism of the population as well as the competition mechanism of the population are represented. The population diversity and population fitness are used as the primary criteria of the population evolution. By competing between the current population and the historical optimal population, the whole population evolution can be done on the basis of the whole population evolution principle of the biologic genetic theory. Prematurity is overcome effectively. Experiments on QoS-aware web services selection show that the genetic algorithm with population diversity handling can get more excellent composite service plan than the standard genetic algorithm.
The work presented in this paper was supported by the National Basic Research and Development Program (973 program) of China under Grant No. 2003CB314806; the National Natural Science Foundation project of China under Grant No. 90204007; the National Natural Science Funds for Distinguished Young Scholar of China under Grant No. 60125101; the program for Changjiang Scholars and Innovative Research Team in University (PCSIRT); BUPT Education Foundation.
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Zhang, C., Su, S., Chen, J. (2006). Efficient Population Diversity Handling Genetic Algorithm for QoS-Aware Web Services Selection. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11758549_14
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