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Titlebook: Engineering Systems and Networks; The Way Ahead for In Marlene Amorim,Carlos Ferreira,Carlos Prado Conference proceedings 2017 Springer Int

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發(fā)表于 2025-3-23 11:32:48 | 只看該作者
Mohammad Alauddin,Clement Allan Tisdellonsumers in order to satisfy their expectations. The main goal of this paper is to propose a mixed integer linear programming (MILP) model that integrates forward and reverse material flows in a retailer’s omnichannel logistics network. The model proposed helps to determine the mix of orders and ret
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發(fā)表于 2025-3-23 16:17:20 | 只看該作者
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發(fā)表于 2025-3-23 19:40:06 | 只看該作者
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發(fā)表于 2025-3-24 01:19:25 | 只看該作者
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發(fā)表于 2025-3-24 05:04:33 | 只看該作者
Subjectivist Theories of Intrinsic Value,endency. To overcome such difficulties and better match SC practices with the context characteristics, the adoption of analytical methods is required. Exploiting the availability of operational data, a four stage data-driven SKU differentiation framework is proposed relying on exploratory factor ana
16#
發(fā)表于 2025-3-24 10:04:58 | 只看該作者
Introduction: Background and History,rate upstream and downstream actions is quite a complex task that involves different levels of difficulty. Several studies have been developed to assess the supply chain management integration (SCMI), with different actions corresponding to integration among chain members; nevertheless, little has b
17#
發(fā)表于 2025-3-24 11:30:17 | 只看該作者
The Environmental Movement in Irelandplant visits—and quantitative methods—using a software and data-driven mapping methods—was used to answer the following question: can lean manufacturing contribute to a company environmental and social sustainability? The conclusions of the research are empirically analysed. As expected the impact o
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發(fā)表于 2025-3-24 17:41:39 | 只看該作者
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發(fā)表于 2025-3-24 20:56:03 | 只看該作者
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發(fā)表于 2025-3-25 01:30:36 | 只看該作者
The Entrepreneurial Dynamics in Italyof OEE factors and maintenance history from a real database. The results suggesting that there is a correlation between the Time Between Stoppages and the trend degree of the Mean and/or the Standard Deviation (SD) of cycle time. This approach intended to help the predictions of shutdowns for maintenance.
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