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Genetic Algorithm Based WEB Service Selection with Multiple Constraints and Preferences

Author: LiLi
Tutor: KongLingFu
School: Yanshan University
Course: Applied Computer Technology
Keywords: Quality of service Service portfolio Global Optimization Dual archive algorithm Preference algorithm Multi - objective Genetic Algorithms
CLC: TP393.09
Type: Master's thesis
Year: 2011
Downloads: 88
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Abstract


With the development of Web services , the service has the same function has a different quality of service has also increased. Select Web service composition which plays a very important role in the face of massive combination of programs , Web services based on global QoS constraints . Users of combined service QoS demanding , sometimes the user needs according to their own preferences area to produce a satisfactory combination of Web services . How to meet global QoS constraints , and solutions to meet user preferences become an important research topic , the specific content of this paper is as follows . First , the optimal selection problem of Web services based on QoS constraints . The combination service support service constraints polymerization QoS calculations . According to the constraint boundary analysis and the feasibility of the individual metrics , feasible solutions and infeasible solutions jointly participate in the evolution of the two - archiving model . Two - archive algorithm according to the model , feasible solutions and infeasible solutions with different selection methods , feasible solutions with non-inferiority classification ranking and crowding select operator selection infeasible solutions based on fitness selection constraint violation through simulated binary crossover operation and mutation operations of the real number to find Pareto optimal solution . Next, the preference-based Web Service Selection . Proposed preference model weight QoS preferences and user interest point - based Web services . According to the model is proposed based on the comparison of preference information , the proposed algorithm based on the preferences of the positive and negative reference point . Non-inferiority ranking based on the fitness value of the program , the algorithm uses the binary tournament selection method , if it has the same level , with positive and negative reference point operator to select close to the positive reference point , the individual away from the negative reference point . The algorithm more viable options in the user area of ??interest . Finally , through the experimental verification of the validity of the above algorithm , and the algorithm for experimental comparison, the algorithm is applied to the Web Services Selection , ideal Pareto optimal solution .

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