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Implementation of various N-dimansional heuristic optimization algorithms such as Nelder Mead simplex, Box, axis search, gradient descent, Newton Rhapson, Hooke Jeeves etc.

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N-dimensional-Optimization-Algorithms

Implementation of various N-dimansional optimizatition algorithms such as Nelder Mead simplex, Box, axis search, gradient descent, Newton Rhapson, Hooke Jeeves etc.

lab1.py

Contains implementation of golden section search (with finding unimodal interval) which is used in other methods for search along an axis.

Contains implementation of Nelder Mead simplex algortihm and Hooke-Jeeves algorithm.

lab2.py

Contains implementation of gradient descent (with calculating gradients on-the-fly), Newton-Raphson method, Box algorithm.

Also includes a method of transforming problem with limitations into a problem without limitations which can then be solved with one of the above methods.

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Implementation of various N-dimansional heuristic optimization algorithms such as Nelder Mead simplex, Box, axis search, gradient descent, Newton Rhapson, Hooke Jeeves etc.

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