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A Novel GA-BP Based Bidding Prediction Algorithm for Contract Logistics of Road Freight Transportation

机译:基于GA-BP的公路货运合同物流竞标预测算法

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In this paper, we propose a novel bidding prediction algorithm based on the hybrid GA (Genetic Algorithm) and BP (Back Propagation) model for contract logistics of road freight transportation. Seven factors of GDP, fuel price, market requirement, cargo weight, transportation distance, carrier, and truck specification are concerned as the major factors. According to the nonlinear nature of transportation cost and carriers' psychological price, the BP neural network is applied to fit the nonlinear features. By training the dataset, GA is good at predicting the short-term bidding prices. In addition, genetic algorithm is integrated into the GA model to improve the long-term searching performance. The hybrid GA-BP algorithm is experimented to be of a good predictor. This study gives implication to 3PL providers that mining previous records with artificial intelligent algorithm is effective and feasible in road freight transportation bidding managements.
机译:本文提出了一种基于杂交GA(遗传算法)和BP(背传播)道路货运物流合同物流的新型招标预测算法。 GDP,燃料价格,市场需求,货物重量,运输距离,载体和卡车规范的七个因素涉及主要因素。 根据运输成本的非线性性质和载体的心理价格,采用BP神经网络适合非线性特征。 通过培训DataSet,Ga善于预测短期竞标价格。 此外,遗传算法集成到GA模型中,以提高长期搜索性能。 混合GA-BP算法实验是一种良好的预测因素。 本研究向3PL提供商致力于采用人工智能算法的先前记录,在公路货运竞标管理中采用先前的记录是有效可行的。

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