Diet problems are optimisation problems where typically several raw materials are combined at minimum cost to make a product, subject to nutrient requirements.
The simplest type of diet problem is the Blending Problem, which was one of the first LPs solved. With the introduction of intermediate mixing bins the Pooling Problem is formed. We look at solving this NLP using SLP. When several factories are combined together we get a large NLP, that we call the Multifactory Problem. We solve this using decomposition by factory. We also look at using decomposition to find the global minimum to this highly nonconvex problem. A further type of diet problem that has integer constraints we call the Silo Problem. This is an MINLP, which we solve by decomposition into NLP and ILP.
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