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A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization

机译:网络企业优化的基于仿真的多目标遗传算法

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摘要

Nowadays, in a hotly competitive environment, companies are continuously trying to provide products and/or services to customers faster, cheaper, and better than the competitors do. Managers have learned that they cannot do it alone; rather, they must work on a cooperative basis with other organizations in order to succeed. Although the resulting enterprise networks are more competitive, the tasks for planning, management and optimization are much more difficult and complex. In this paper, we present a newly developed toolbox "ONE" to support decision makers for the assessment, design and improvement of such supply chain networks. The toolbox comprises innovative and user-friendly concepts related to the modeling, simulation and optimization of modern enterprise networks. Two case studies, proposed by partners from automotive and textile industries, are presented and computational results analysed.
机译:如今,在竞争激烈的环境中,公司不断尝试比竞争对手更快,更便宜,更好地向客户提供产品和/或服务。经理们知道,他们不能独自做到这一点。相反,他们必须与其他组织合作才能成功。尽管最终的企业网络更具竞争力,但计划,管理和优化任务却更加困难和复杂。在本文中,我们提出了一个新开发的工具箱“ ONE”,以支持决策者评估,设计和改进此类供应链网络。该工具箱包含与现代企业网络的建模,仿真和优化有关的创新且用户友好的概念。介绍了汽车和纺织行业合作伙伴提出的两个案例研究,并对计算结果进行了分析。

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