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首页> 外文期刊>Journal of Theoretical and Applied Information Technology >A METAHEURISTIC APPROACH FOR STATIC SCHEDULING BASED ON CHEMICAL REACTION OPTIMIZER
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A METAHEURISTIC APPROACH FOR STATIC SCHEDULING BASED ON CHEMICAL REACTION OPTIMIZER

机译:基于化学反应优化器的静态调度元算法

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Over the past several decades, scheduling has emerged as an area of critical research, thereby constituting a requisite process for myriad applications in real life. In this regard, many researchers have experimented and utilized various optimization algorithms to obtain optimized schedules. It is also noteworthy that the concepts of some optimization algorithms are essentially derived from nature. This paper aims to augment a compiler using a chemical reaction optimizer in order to identify an optimized instructions static schedule capable of being used within both single and multicore computer systems. This scheduling algorithm, which is denoted as SS-CRO (static scheduling using chemical reaction optimizer), is unique in that it provides alternative schedules involving different costs. Subsequently, SS-CRO tests the schedules in accordance with different types of instructions dependencies before making an appropriate selection. SS-CRO demonstrates that it can not only provide different schedule orders, but also make a competent selection of accepted solutions, whilst dismissing the inappropriate ones in a reasonable span of time. So, this paper presents SS-CRO algorithm that is used to obtain an optimized static scheduling, where SS-CRO has been implemented and evaluated analytically and experimentally. As analytical results, the number of steps for the SS-CRO approximately is O(Num_iteration?CROFun), where CROFun is the number of steps of the selected function. In the experiments results, SS-CRO achieved better execution time and higher accepted solutions in comparison with other optimization algorithms such as; SS-DA (static scheduling using duelist algorithm) and SS-GA (static scheduling using genetic algorithm). Furthermore, SS-CRO achieved the maximum percentage of number of solutions with respect to the execution time of all experiments for all proposed input cases, which is ranged as (10%-30%).
机译:在过去的几十年中,调度已成为一项重要的研究领域,从而构成了现实生活中无数应用的必要过程。在这方面,许多研究人员已经进行了实验并利用了各种优化算法来获得优化的时间表。还值得注意的是,某些优化算法的概念本质上是从自然派生的。本文旨在使用化学反应优化器来增强编译器,以识别能够在单核和多核计算机系统中使用的优化指令静态调度表。这种调度算法称为SS-CRO(使用化学反应优化器的静态调度),其独特之处在于它提供了涉及不同成本的替代调度。随后,SS-CRO在进行适当的选择之前,根据不同类型的指令依存关系对时间表进行测试。 SS-CRO证明,它不仅可以提供不同的计划订单,还可以对可接受的解决方案进行有力的选择,同时在合理的时间内消除不适当的解决方案。因此,本文提出了一种SS-CRO算法,该算法用于获得优化的静态调度,其中SS-CRO已实现并经过分析和实验评估。作为分析结果,SS-CRO的步数大约为O(Num_iteration?CROFun),其中CROFun是所选函数的步数。在实验结果中,与其他优化算法相比,SS-CRO获得了更好的执行时间和更高的可接受解决方案。 SS-DA(使用Duelist算法的静态调度)和SS-GA(使用遗传算法的静态调度)。此外,对于所有建议的输入案例,SS-CRO在所有实验的执行时间方面都达到了解决方案数量的最大百分比,范围为(10%-30%)。

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