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Global Optimization Toolbox For Maple
Optimization is the science of finding solutions that satisfy complicated constraints and objectives. In engineering, constraints may arise from technical issues. In business, constraints are related to many factors, including cost, time, and staff. The objective of global optimization is to find [numerically] the absolute best solution of highly nonlinear optimization models that may have a number of locally optimal solutions. Global optimization problems can be extremely difficult. Frequently engineers and researchers are forced to settle for solutions that are “good enough” at the expense of extra time, money, and resources, because the best solution has not been found. Using the Global Optimization Toolbox, you can formulate your optimization model easily inside the powerful Maple numeric and symbolic system, and then use world-class Maple numeric solvers to return the best answer, fast! Illustrative references: 1. Pintér, J. D. Global Optimization in Action. Springer Science, 1996, 512 p., ISBN: 978-0-7923-3757-7 Winner of the 2000 INFORMS Computing Society Prize. 2. Pintér, J. D., Linder, D. and Chin, P. Global Optimization Toolbox for Maple: An introduction with illustrative applications. Optimization Methods and Software 21 (2006) (4) 565-582.
More informationMastrave
Mastrave is a free software library written to perform vectorized scientific computing and to be as compatible as possible with both GNU Octave and Matlab computing frameworks, offering general purpose, portable and freely available features for the scientific community. Mastrave is mostly oriented to ease complex modelling tasks such as those typically needed within environmental models, even when involving irregular and heterogeneous data series. The set of array-based semantic constraints provided by the library implements the standard semantic support for the Semantic Array Programming (SemAP) paradigm [http://mfkp.org/INRMM/tag/semap]. This support is meant to allow concise pieces of array-programming code to be immersed within a semantic network of array-concepts, without renouncing to extremely compact representations. Based on the mathematics of arrays, the semantics of the SemAP constraints is inherently portable. A rich set of semantic constraints is natively implemented in GNU Octave/MATLAB by the Mastrave modelling library and is easily accessed in other programming languages via multi-language array programming bridges (e.g. in Python and GNU R). For a simplified summary of some core concepts, you may read https://dx.doi.org/10.6084/m9.figshare.3472661
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