Combine automatic and manual process on web service selection and composition to support QoS

An original GA (genetic algorithm) is usually used for QoS (quality of service)-based Web services selection, however, such algorithm has to do a large redundancy repeat to find a solution for the reason that it does not make use of adequate output information. Thus, the efficiency and precision of GA are reduced. Moreover, fixed fitness function can not change to fit for different composite situations and complete automatic process so GA sometimes would miss the most suitable solution. To remedy this situation, this paper proposes a novel algorithm GBAA (genetic based ant algorithm) which could put feedback information to original GA by using MMAS (max-min ant system) and it also overcome some drawbacks of MMAS such as long time need and slow convergence. The new approach could gain the benefits of both GA and MMAS. Besides GBAA DC (divide and composite) method and rank sort method are added. DC is adopted to analysis business requirement and to build process. After computing QoS attributes, a manual step is allowed to put into selection process and a rank sort method is used to distinguish profits of different solutions. The automatic process which is cooperated with manual process could help user to make more effective decisions on Web service selection.