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A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem

机译:解决项目调度问题的多样性自适应混合进化算法

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In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each project activity. To solve the problem, we propose a hybrid evolutionary algorithm. This algorithm incorporates a diversity-adaptive simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the fluctuation of diversity of evolutionary algorithm population. The performance of the hybrid evolutionary algorithm on six different instance sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid evolutionary algorithm significantly outperforms the previous algorithms.
机译:在本文中,我们解决了项目调度问题。这个问题考虑了项目经理的优先级优化目标。该目标意味着为每个项目活动分配最有效的人力资源。为了解决这个问题,我们提出了一种混合进化算法。该算法将分集自适应模拟退火算法结合到进化算法的框架中,旨在提高进化搜索的性能。模拟退火算法根据进化算法种群多样性的波动来适应其行为。将混合进化算法在六个不同实例集上的性能与文献中先前提出的用于解决该问题的算法的性能进行比较。获得的结果表明,混合进化算法明显优于以前的算法。

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