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首页> 外文会议>International Conference on Cloud Computing and Security >A Hybrid Artificial Bee Colony Algorithm to Solve Multi-objective Hybrid Flowshop in Cloud Computing Systems
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A Hybrid Artificial Bee Colony Algorithm to Solve Multi-objective Hybrid Flowshop in Cloud Computing Systems

机译：解决云计算系统多目标混合Flowshop的混合人工蜂群算法

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摘要

This paper proposes a local search enhanced hybrid artificial bee colony algorithm (LABC) for solving the multi-objective flexible task scheduling problem in Cloud computing system. The task scheduling is modeled as a hybrid flow shop scheduling (HFS) problem. In multiple objectives HFS problems, three objectives, i.e., minimum of the makespan, maximum workload, and total workload are considered simultaneously. In the proposed algorithm, each solution is represented as an integer string. A deep-exploitation function is developed, which is used by the onlooker bee and the best food source found so far to complete a deep level of search. The proposed algorithm is tested on sets of the well-known benchmark instances. Through the analysis of experimental results, the highly effective performance of the proposed LABC algorithm is shown against several efficient algorithms from the literature.
机译：针对云计算系统中的多目标柔性任务调度问题，提出了一种局部搜索增强型混合人工蜂群算法。任务调度被建模为混合流水车间调度（HFS）问题。在多目标HFS问题中，同时考虑了三个目标，即最小制造期，最大工作量和总工作量。在提出的算法中，每个解决方案都表示为一个整数字符串。开发了一种深度开发功能，供围观蜂和迄今发现的最佳食物来源使用，以完成更深入的搜索。所提出的算法在一组著名的基准实例上进行了测试。通过对实验结果的分析，与文献中的几种有效算法相比，所提出的LABC算法具有很高的性能。

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