Abstract
The problem of QoS-aware multiobjective optimization is an important issue for Web services selection in distributed computing environment. In this paper, a novel algorithm called MOASS (multiobjective optimization algorithm for web service selection) is proposed through analyzing the genetic operators such as constraint handling, the initial population generation, fitness assignment, and diversity preservation. Compared with MOEAWP (Yu et al., 2007), simulation results show that the feasible objective region can be filled uniformly with the optimal solutions obtained by MOASS under different test applications. In the case of higher constraints especially, MOASS can obtain more high-quality and evenly distributed nondominated solutions than MOEAWP.
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