A Proposal of a Mathematical Roadmap for Scilab DRAFT - Projects
A Proposal of a Mathematical Roadmap for Scilab DRAFT - Projects
A Proposal of a Mathematical Roadmap for Scilab DRAFT - Projects
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4.3 Suggested library to connectOPT++ opt++ is a library <strong>of</strong> nonlinear optimization algorithms written in C++.The motivation <strong>for</strong> this package is to build an environment <strong>for</strong> the rapid prototypingand development <strong>of</strong> new optimization algorithms. In particular, the focus is onrobust and efficient algorithms <strong>for</strong> problems in which the function and constraintevaluations require the execution <strong>of</strong> an expensive computer simulation. Currently,OPT++ includes the classic Newton methods, a nonlinear interior-point method,parallel direct search, generating set search, a trust region - parallel direct searchhybrid, and a wrapper to NPSOL. Between these methods, a wide range <strong>of</strong> problemscan be solved, e.g. with or without constraints, with or without analytic gradients,simulation based, etc. OPT++ 2.4 is now available on a variety <strong>of</strong> plat<strong>for</strong>ms underthe GNU Lesser General Public License” Opt++ is developed at CSMR Department<strong>Projects</strong> at Sandia National Labs in Cali<strong>for</strong>nia by Patty Hough, Juan Meza, RicardoOliva, Pam Williams.OPT ++ is available under the GNU Lesser General Public License. It is ported<strong>for</strong> Linux, Cygwin.Coin-OR (more specifically CLP and CBC) is a linear programming library cando mixed integer programming, supports sparse matrixes and was be<strong>for</strong>e 2004 acommercial product from IBM (OSL). This library was competing (and is still competing)with CPLEX. Interface to CLP is the subject <strong>of</strong> SEP #6 by Yann Collette: SEP clp4.4 Existing tools which may require an updateConMinis a <strong>for</strong>tran routine written by G. Vanderplaats at NASA <strong>for</strong> Nastran.ConMinis behind every optimization per<strong>for</strong>med with Nastran. This optimization methodallows to per<strong>for</strong>m constrained optimization and is based on the feasible directionsmethod (no problem with a Hessian matrix, only vectors are stored). A first toolboxhas been written to interface this method to <strong>Scilab</strong>. Contribution 10864.5 Current projects to provide the featureThe sci-ipopt project aims at providing an interface to IPOPT : sci-ipoptThe fmincon project aims at providing the fmincon function in <strong>Scilab</strong>, by usingthe ipopt solver : fmincon5 ModelizationThis is a list <strong>of</strong> missing features in <strong>Scilab</strong>:• non linear modelling: neural networks, Kriging, statistical modeling;• linear modelling: LASSO <strong>for</strong> example;14