A GRASP-Simulated Annealing approach applied to solve Multi-Processor Task Scheduling problems

2019 14th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2019-12-01 DOI:10.1109/ICCES48960.2019.9068118

Abla F. A. Saad, A. Kafafy, Osama Abd El Raouf, N. El-Hefnawy

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引用次数: 2

Abstract

Task scheduling in Parallel processing systems is considered as one of the most difficult NP-hard optimization problems, it represents the most critical issue in managing multiprocessors. The greatest challenge in these problems is to find the best schedule for these tasks in a reasonable amount of time. This paper introduces a new hybrid metaheuristic algorithm called GRASP-Simulated annealing (GRASP-SA) to handle such problems. In this proposal, GRASP algorithm is modified by adopting Simulated Annealing procedure instead of classical local search procedure used in GRASP. This means, Improving the classical GRASP through adding more capabilities to escape local optima. To identify the influence of the proposed modifications, GRASP-SA is verified against the original GRASP, the original Simulated Annealing (SA), and the recently developed GRASP-GA. a set of benchmark problems are adopted in this experiment. The results indicate the proposed GRASP-SA has two-fold superiority over its competitors, it can achieve the schedule with the minimum make span through the minimum running time for most test problems.

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应用模拟退火方法求解多处理机任务调度问题

并行处理系统中的任务调度是最困难的NP-hard优化问题之一，它代表了多处理器管理中最关键的问题。在这些问题中，最大的挑战是在合理的时间内为这些任务找到最佳的时间表。本文提出了一种新的混合元启发式算法，称为grasp -模拟退火(GRASP-SA)来处理这类问题。本文采用模拟退火过程代替传统的局部搜索过程，对GRASP算法进行了改进。这意味着，通过添加更多功能来逃避局部最优，从而改进经典的GRASP。为了确定所提出的修改的影响，对原始的GRASP、原始的模拟退火(SA)和最近开发的GRASP- ga进行了验证。本实验采用了一组基准问题。结果表明，所提出的GRASP-SA算法在大多数测试问题上都能以最小的运行时间实现最短的工期，比同类算法具有两倍的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 14th International Conference on Computer Engineering and Systems (ICCES)

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