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Optimization Algorithms for the Top-k Partners Selection Problem in Dynamic Alliance

机译:动态联盟中Top-K合作伙伴选择问题的优化算法

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Establishing efficient partnership in dynamic alliance is a fundamental process in the supply chain management (SCM). In the past, the state-of-the-art researches mainly focused on establishing effective factors selection model to evaluate candidate enterprises. While there are large numbers of candidate enterprises and a lot of concerned factors, it is a challenge for the SCM system in selecting proper cooperative partners accurately and efficiently. In order to speed up the process of selection, an optimization top-k algorithm for partner selection is proposed in this paper. Two optimization methods-OP (Optimization Procedure) and IMOP (IMproved Optimization Procedure) are provided for classifying the factors and sorting the candidate enterprises. The experiment shows that optimization top-k algorithm significantly reduces the time of partner selection and improves the accuracy.
机译:在动态联盟中建立有效的伙伴关系是供应链管理(SCM)的基本进程。 过去,最先进的研究主要集中在建立有效因素选择模型来评估候选企业。 虽然有大量的候选企业和很多有关的因素,但对于精确有效,有效地选择适当的合作伙伴的SCM系统是一项挑战。 为了加快选择过程,本文提出了一种优化TOP-K伙伴选择算法。 提供了两种优化方法-OP(优化程序)和IMOP(改进的优化程序),用于对候选企业进行分类和分类。 该实验表明,优化Top-K算法显着降低了合作伙伴选择的时间并提高了准确性。

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