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Data envelopment analysis models to support the selection of vehicle routing software for city logistics operations

机译:数据包络分析模型可支持选择用于城市物流运营的车辆路线选择软件

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In city logistics operations, vehicle routing is critical for successful freight delivery execution. Optimal routing, however, may not be performed when manual routing methods are implemented, due to their inability to cope with a number of delivery constraints such as hard delivery time windows. The use of an automated vehicle routing software by freight carriers, is usually the preferred option, as it may increase customer service and reduce operational costs. The evaluation and selection of automated routing software has become increasingly difficult for decision makers due to a large number of software products available and the great variety of features and capabilities they offer. This paper first develops a data model to capture all the significant attributes that characterize a routing software. The attributes are measured with ordinal data as they mainly express qualitative issues. Then, it presents a data envelopment analysis (DEA) model that aids the selection procedure by estimating the index Total Performance/Price that expresses the commonly used “value for money” criterion. This index is able to identify those routing software that are considered as best buys. Moreover, this paper proposes a DEA model to distinguish the best alternative from the “best buys” cases. A case study illustrates the proposed methodology.
机译:在城市物流运营中,车辆路线对于成功执行货运至关重要。但是,当实施手动路由方法时,可能无法执行最佳路由,这是因为它们无法应对许多交付限制,例如硬交付时间窗口。通常首选货运公司使用自动车辆路线选择软件,因为它可以增加客户服务并降低运营成本。由于大量可用的软件产品以及它们提供的多种功能,决策者对自动路由软件的评估和选择变得越来越困难。本文首先开发了一个数据模型,以捕获表征路由软件的所有重要属性。这些属性使用序数数据进行度量,因为它们主要表示定性问题。然后,它提出了一个数据包络分析(DEA)模型,该模型通过估算表示总的“物有所值”标准的总绩效/价格指数来辅助选择过程。该索引能够识别那些被认为是最佳购买的路由软件。此外,本文提出了一种DEA模型,以区分“最佳购买”案例中的最佳替代方案。案例研究说明了所提出的方法。

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