Titlebook: Operations Research Proceedings 2016; Selected Papers of t Andreas Fink,Armin Fügenschuh,Martin Josef Geiger Conference proceedings 2018 Sp

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书目名称Operations Research Proceedings 2016影响因子(影响力)




书目名称Operations Research Proceedings 2016影响因子(影响力)学科排名




书目名称Operations Research Proceedings 2016网络公开度




书目名称Operations Research Proceedings 2016网络公开度学科排名




书目名称Operations Research Proceedings 2016被引频次




书目名称Operations Research Proceedings 2016被引频次学科排名




书目名称Operations Research Proceedings 2016年度引用




书目名称Operations Research Proceedings 2016年度引用学科排名




书目名称Operations Research Proceedings 2016读者反馈




书目名称Operations Research Proceedings 2016读者反馈学科排名

消耗

On- and Offline Scheduling of Bidirectional Trafficing of vehicles in opposite direction is restricted. The considerations are motivated by the ship traffic at the Kiel Canal which connects the North and Baltic Seas and is operated bidirectionally. Since ships register their travel requests only on short notice, we investigate the Canal’s ship traff

Canopy

Integrated Segmentation of Supply and Demand with Service Differentiations end, it establishes a joint perspective on the market side—that is, prices and service levels—and the operations side—that is, the inventory management policy and the corresponding parameters. This joint perspective comprises analyzing when the introduction of a service-level menu increases profit

kidney

AND

扩张

Integrated Location-Inventory Optimization in Spare Parts Networksloped, formulated as linear program (LP) and finally, embedded into a set-covering problem framework. The resulting model is a mixed integer linear program (MILP) which integrates (1) strategic facility choice, (2) tactical base-stock level setting and (3) operational sourcing decisions. Due to the

斗争

Analogy

繁重

Improving the Forecasting Accuracy of 2-Step Segmentation Models(HB) models, which estimate consumers’ individual preferences is nowadays state-of-the-art. However, the knowledge of consumer preferences on a less disaggregated level, like segment-level, is key for demand predictions of non-customized products. Clustering individual HB data to achieve segment-lev

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