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A novel Bi-Ant colony optimization algorithm for solving multi-objective service selection problem

机译:一种解决多目标服务选择问题的新型Bi-蚁群算法

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The multi-objective service selection problem is a basic problem in Service Computing and is NP-Hard. This paper proposes a novel Bi-Ant colony optimization multi-objective service selection algorithm for this problem. Two objective functions related with response time and cost attributes are considered. For each objective, a heuristic function and a pheromone updating policy are defined against the characteristics of this problem. Then, a combined state transition rule is designed based on them. The algorithm has been tested in nine cases and compared with the related MOACO algorithm for this problem. The result demonstrates that our approach is effective and better than MOACO.
机译:多目标服务选择问题是服务计算中的一个基本问题,是NP-Hard。针对这一问题,本文提出了一种新颖的双蚁群优化多目标服务选择算法。考虑了与响应时间和成本属性相关的两个目标函数。针对每个目标,针对此问题的特征定义了启发式函数和信息素更新策略。然后,基于它们设计组合状态转移规则。该算法已在9种情况下进行了测试,并与相关的MOACO算法进行了比较以解决此问题。结果表明,我们的方法有效且优于MOACO。

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