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This item implements a linear model predictive controller. Specifically, it solves a specific quadratic system working with the method described from the paper: A Fast Gradient strategy for embedded linear predictive Command (2011) by Markus Kogel and Rolf Findeisen
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This function is definitely an implementation in the Hungarian algorithm (also know since the Kuhn-Munkres algorithm) which runs in O(N^3) time. It solves the optimal assignment problem. Such as, suppose you might have an equal amount of staff and Employment and you might want to decide which staff to assign to which Work.
Acknowledge: if the danger is high, one demands to just accept the pitfalls but will also require to say the reason for acceptance.
Observe that there is no must check for self-assignment in a duplicate-constructor. This is because the copy constructor is barely known as when new objects are increasingly being made, and there is no method to assign a recently produced item to itself in a method that phone calls to copy constructor.
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This process makes use of an number of memory that is definitely linear in the volume of variables to get optimized. So it is able to dealing with issues with a really big variety of variables. Having said that, it is mostly not so good as the L-BFGS algorithm (see the lbfgs_search_strategy course).