This will give an overview of optimization features available in scilab.I focus on user's point of view that is we have to minimize and maximize an objective function and must find a solver suitable for the problem.This gives an overview of what problems can be solved by scilab and what behaviour can be expected for those solvers.I will be trying to minimize/maximize a given cost function f(x) with or without constraints.Scilab is able to deal with 4 types of problems:
i)Linear problems with linear constraints
ii)Quadratic problems with linear constraints
iii)Non-linear problems without constraints using "fminsearch"
iv)Non-linear problems without constraints using "optim"