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We present in this paper an overview of optimization algorithms available in the Scilab software. We focus on the user's point of view, that is, we have to minimize or maximize an objective function and must find a solver suitable for the problem. The aim of this paper is to give a simple but accurate view of what problems can be solved by Scilab and what behavior can be expected for those solvers. For each solver, we analyze the type of problems that it can solve as well as its advantages and limitations. In order to compare the respective performances of the algorithms, we use the CUTEr library, which is available in Scilab. Numerical experiments are presented, which indicates that there is no cure-for-all solvers.
Date of Conference: 18-20 Sept. 2009