The complexity within supply chains has increased enormously in the last couple of decades. Matching this complexity with solutions that make the trade-off between results and acceptance within the company, is a challenge that drives many researchers and practitioners in the field of the supply chain. To succeed in this challenge, efficient optimization algorithms has gained a lot of attention in the last 70 years. One of the most powerful fields in optimization was machine learning.
However, only since the increasing computing power and the exponential growth of data over the last years, makes up the fact that machine learning gained interests only more recently. This rapid growth of machine learning had the pitfall of creating a buzzword, rather than a good tool to really help companies in their supply chain activities. Especially when talking about demand planning and forecasting.
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