A Hybrid Multiobjective Discrete Particle Swarm Optimization Algorithm for a SLA-Aware Service Composition Problem
A Hybrid Multiobjective Discrete Particle Swarm Optimization Algorithm for a SLA-Aware Service Composition Problem
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DOI：
10.1155/2014/252934
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发表时间：
2014-01
影响因子：
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通讯作者：
Hao Yin;Changsheng Zhang;Bin Zhang;Ying Guo;Tingting Liu
中科院分区：
文献类型：
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作者：
Hao Yin;Changsheng Zhang;Bin Zhang;Ying Guo;Tingting Liu
针对sla感知服务组合问题（SSC），建立了该算法的优化模型，提出了混合多目标离散粒子群优化算法（HMDPSO）。根据该问题的特点，引入交叉算子，设计了粒子更新策略。为了抑制粒子群的过早收敛，提高粒子群的全局搜索能力，引入了群体多样性指标，并提出了一种粒子突变策略来增加群体多样性。为了加快获取可行粒子位置的速度，提出了一种基于约束支配的局部搜索策略，并将其引入到该算法中。最后，对HMDPSO算法中的一些参数进行了分析，并设置了相应的合适值，然后对HMDPSO算法和HMDPSO算法进行了比较
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