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Scheduling Tasks with Non-negligible Intertask Communiction onto Multiprocessors by using Genetic Algorithms

机译:使用遗传算法将任务间通信不可忽略的任务调度到多处理器上

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The paper deals with genetic algorithms for scheduling the tasks with non-negligible intertask communication. Three genetic algorithms for scheduling with the primary goal to minimise finishing time are reported. The basic genetic algorithm includes the reproduction, crossover and mutation operators. Its improved version has additional cloning operator that allows duplicated scheduling. The third algorithm is adaptive. The experiments describing influence of genetic operators' probabilities, population size and number of generations on the resulting schedules, comparison of algorithms and the results obtained for different task granulation are discussed.
机译:本文讨论了用于通过不可忽略的任务间通信来调度任务的遗传算法。报告了三种用于调度的遗传算法,其主要目标是最大程度地减少完成时间。基本的遗传算法包括复制,交叉和变异算子。它的改进版本具有附加的克隆运算符,允许重复的计划。第三种算法是自适应的。讨论了描述遗传算子的概率,种群规模和世代数对所得时间表的影响的实验,算法比较以及针对不同任务制粒获得的结果。

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