Ant Colony optimization Algorithm for Workforce Planning: Influence of the Evaporation Parameter

S. Fidanova, Gabriel Luque, O. Roeva, M. Ganzha
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引用次数: 1

Abstract

Optimization of the production process is important for every factory or organization. The better organization can be done by optimization of the workforce planing. The main goal is decreasing the assignment cost of the workers with the help of which, the work will be done. The problem is NP-hard, therefore it can be solved with algorithms coming from artificial intelligence. The problem is to select employers and to assign them to the jobs to be performed. The constraints of this problem are very strong and for the algorithms is difficult to find feasible solutions. We apply Ant Colony Optimization Algorithm to solve the problem.We investigate the algorithm performance according evaporation parameter. The aim is to find the best parameter setting.
劳动力规划的蚁群优化算法:蒸发参数的影响
生产过程的优化对每个工厂或组织都很重要。通过对劳动力规划的优化,可以实现更好的组织。主要目标是降低工人的分配成本,在此帮助下,工作将完成。这个问题是np困难的,因此可以用来自人工智能的算法来解决。问题是选择雇主并将他们分配到要执行的工作。该问题的约束条件很强,算法很难找到可行的解。我们采用蚁群优化算法来解决这个问题。根据蒸发参数考察了算法的性能。目的是找到最佳的参数设置。
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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