Service provider portfolio selection (SPPS) can be a major challenge for organizations to achieve project success. Hence, organizations need to decide on which service provider portfolio (SPP) is appropriate for project management (PM). However, there has been limited research on how to select a SPP in PM. To address this research gap, we establish a novel model for SPPS based on a BP neural network integrated with entropy-AHP from the perspective of the comprehensive economic benefit. This model employs a BP neural network due to its robustness and memory and nonlinear mapping abilities. Furthermore, we implement the proposed model for a construction project to verify the effectiveness. Our results indicate that the model performs well with a prediction accuracy of 97%. Moreover, the model is confirmed to be robust as it still achieves high prediction accuracy when the input data are disturbed randomly.

中文翻译：

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使用 BP 神经网络进行项目管理的服务提供商组合选择

服务提供商组合选择 (SPPS) 可能是组织实现项目成功的主要挑战。因此，组织需要决定哪个服务提供商组合 (SPP) 适合项目管理 (PM)。然而，关于如何在 PM 中选择 SPP 的研究有限。为了解决这一研究空白，我们从综合经济效益的角度建立了一种基于 BP 神经网络与熵-层次分析法相结合的 SPPS 新模型。由于其鲁棒性和记忆力以及非线性映射能力，该模型采用了 BP 神经网络。此外，我们为一个建设项目实施了建议的模型，以验证其有效性。我们的结果表明该模型表现良好，预测准确率为 97%。而且，