Solving multiprocessor scheduling problem using multi-objective mean field annealing
Solving multiprocessor scheduling problem using multi-objective mean field annealing
复制标题
使用多目标平均场退火解决多处理器调度问题
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
A. Acan
中科院分区：
文献类型：
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作者：
Nasser Lotfi;A. Acan
多处理机调度问题是并行程序设计和分布式系统环境中的重要问题之一。多处理器调度被认为是一个NP难问题，因此，不推荐使用精确解方法。单目标型多处理机调度问题已被遗传算法、蚁群算法、粒子群算法、平均场退火算法等进化算法所解决，本文提出了一种求解多目标型多处理机调度问题的平均场退火算法。我们引入了三个目标的多目标多处理机调度问题，然后用平均场退火算法求解。最后，该算法在一些基准测试和NSGA2和莫加算法的有效性进行了比较。结果表明，平均场退火方法在合理的计算时间内产生更好的Pareto前沿。
Multiprocessor scheduling problem is one of the most important issues regarding to parallel programming and distributed system environments. Multiprocessor scheduling is known as a NP-hard problem, hence, applying an exact solution method is not recommended at all. Single-objective type of multiprocessor scheduling problem has already been solved by evolutionary algorithms like genetic algorithms, ant colony optimization, particle swarm optimization, mean field annealing and so on. This paper presents a mean field annealing approach for solving the multi-objective type of this problem. We introduce multi-objective multiprocessor scheduling problem with three objectives and then solve it using mean field annealing approach. Finally, the proposed algorithm is tested over some benchmarks and its effectiveness is compared to NSGA2 and MOGA algorithms. Obtained results show that mean field annealing method leads better Pareto fronts within reasonable computation times.