Fuzzy-guided genetic algorithm applied to the web service selection problem
Min Chen, Simone A. Ludwig · 2012
The benefits of Quality of Service (QoS) aware service selection is undisputed. The selection process based on QoS allows the user to specify their requirements not only based on functional attributes but also on non-functional attributes. The automation of this selection process can be done via optimization. Several different exact but also approximate algorithms have been proposed in the past. Genetic algorithm is one such method that can find approximate solutions during the service selection task. In this paper, we propose an improved version of the standard genetic algorithm approach by making use of fuzzy logic during the stochastic genetic search process. The fuzzy component dynamically adjusts the crossover and mutation rates of the evolution for every ten consecutive generations. Results show that the fuzzy-guided Genetic algorithm approach improves the solution quality.