QoS-Aware Multiobjective Optimization Algorithm for Web Services Selection with Deadline and Budget Constraints | Zendy

Han Xianzhong | Zendy; Yuan Yingchun | Zendy; Chen Chen | Zendy; Wang Kejian | Zendy

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QoS-Aware Multiobjective Optimization Algorithm for Web Services Selection with Deadline and Budget Constraints

Author(s) -

Han Xianzhong,

Yuan Yingchun,

Chen Chen,

Wang Kejian

Publication year - 2014

Publication title -

advances in mechanical engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.318

H-Index - 40

ISSN - 1687-8132

DOI - 10.1155/2014/361298

Subject(s) - computer science , selection (genetic algorithm) , mathematical optimization , quality of service , genetic algorithm , population , web service , constraint (computer aided design) , multi objective optimization , optimization problem , distributed computing , algorithm , mathematics , computer network , artificial intelligence , demography , geometry , sociology , world wide web

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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