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Titlebook: Computational Management; Applications of Comp Srikanta Patnaik,Kayhan Tajeddini,Vipul Jain Book 2021 The Editor(s) (if applicable) and The

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發(fā)表于 2025-3-23 13:14:44 | 只看該作者
https://doi.org/10.1007/978-94-010-1623-0ing. This paper discusses the optimum scheduling for a part of supply chain system using an EOQ model where the demand is dynamic varies with time and one of the promotional effort in the form of a two-stage trade credit is considered. The applicability of the model can be well understood through th
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發(fā)表于 2025-3-23 15:43:52 | 只看該作者
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發(fā)表于 2025-3-23 18:48:18 | 只看該作者
Gross Domestic Product Modeling Using “Panel-Data” Concept condition of Europe from the statistical point of view. The results indicate that the random effects model is more appropriate than fixed effects model. In addition, this chapter also contains a panel data regression model with cross-sectional dependence, heteroscedasticity and also considers serially correlated disturbances for random effects.
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發(fā)表于 2025-3-24 02:05:20 | 只看該作者
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發(fā)表于 2025-3-24 08:53:33 | 只看該作者
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發(fā)表于 2025-3-24 12:54:14 | 只看該作者
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發(fā)表于 2025-3-24 15:53:13 | 只看該作者
Book 2021a wide range of intelligent and optimization techniques, reporting in detail on their application to real-world problems relating to portfolio management and demand forecasting, decision making, knowledge acquisition, and supply chain scheduling and management..
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發(fā)表于 2025-3-24 19:04:06 | 只看該作者
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發(fā)表于 2025-3-24 23:55:14 | 只看該作者
Jeunes adultes et courtes peines, algorithms, we are introducing a well-tuned approach that can solve the challenging MPMCPITC problem. In our portfolios’ applications, we use real-world data and, along with some of the best memetic meta-heuristic and commercial methods, we provide a solution to the MPMCPITC problem, and we compare their solutions to each other.
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