Computer Science ›› 2019, Vol. 46 ›› Issue (2): 187-195.doi: 10.11896/j.issn.1002-137X.2019.02.029

• Artificial Intelligence • Previous Articles     Next Articles

Multi-attribute Decision Making and Adaptive Genetic Algorithm for Solving QoS Optimization of Web Service Composition

LU Cheng-hua1,2, KOU Ji-song1   

  1. College of Management and Economics,Tianjin University,Tianjin 300072,China1
    College of Pearl River,Tianjin University of Finance and Economics,Tianjin 301811,China2
  • Received:2018-03-30 Online:2019-02-25 Published:2019-02-25

Abstract: With the increasing of service-oriented computing,the research on Web service composition based on quality of service (QoS) becomes an inevitable trend.With respect of the multi-dimensional nature and mutual contradiction,this paper transformed the optimization of Web service composition based on QoS into the problem of multi-attribute decision making to resolve it.The distances of each solution to the positive ideal solution (PIS) and the negative ideal solution (NIS) were summed up by means of a compromise coefficient.Finally,a set of ranked Web services were provided to users for a flexible choice.The traditional multi-attribute decision making method can not effectively solve the large-scale search space of Web service composition.Therefore,in order to solve the NP-hard problem of Web service composition optimization better,this paper developed an approach combining the multi-attribute decision making and adaptive genetic algorithm (MADMAGA).The experiments were conducted on a real and comprehensive QoS dataset.The experimental results indicate that the method can find the globally optimal solution in a short period of time.The ranking result of solutions is close to the true sort.Moreover,the proposed method has better scalability for solving the large-scale problem of Web service composition optimization.

Key words: Genetic algorithm, Multi-attribute decision making, Quality of service, Web service composition

CLC Number: 

  • TP301
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