A Hybrid Multiobjective Discrete Particle Swarm Optimization Algorithm for a SLA-Aware Service Composition Problem

For SLA-aware service composition problem (SSC), an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO) is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is des...

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Vydané v:Mathematical problems in engineering Ročník 2014; číslo 1
Hlavní autori: Yin, Hao, Zhang, Changsheng, Zhang, Bin, Guo, Ying, Liu, Tingting
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Hindawi Publishing Corporation 01.01.2014
John Wiley & Sons, Inc
Predmet:
Algorithms
Atoms & subatomic particles
Candidates
Composition
Concrete
Convergence
Heuristic
Linear programming
Mathematical models
Multiple objective analysis
Mutation
Mutations
Objectives
Optimization
Optimization models
Particle swarm optimization
Position indicators
Quality of service
Search methods
Searching
Service oriented architecture
Strategy
Swarm intelligence
ISSN:1024-123X, 1563-5147
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Shrnutí:For SLA-aware service composition problem (SSC), an optimization model for this algorithm is built, and a hybrid multiobjective discrete particle swarm optimization algorithm (HMDPSO) is also proposed in this paper. According to the characteristic of this problem, a particle updating strategy is designed by introducing crossover operator. In order to restrain particle swarm’s premature convergence and increase its global search capacity, the swarm diversity indicator is introduced and a particle mutation strategy is proposed to increase the swarm diversity. To accelerate the process of obtaining the feasible particle position, a local search strategy based on constraint domination is proposed and incorporated into the proposed algorithm. At last, some parameters in the algorithm HMDPSO are analyzed and set with relative proper values, and then the algorithm HMDPSO and the algorithm HMDPSO+ incorporated by local search strategy are compared with the recently proposed related algorithms on different scale cases. The results show that algorithm HMDPSO+ can solve the SSC problem more effectively.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1024-123X
1563-5147
DOI:10.1155/2014/252934