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The following MATLAB code gives a BBO implementation for minimizing the 20-dimensional Rosenbrock function. Note that the following code is very basic, although it does include elitism. Note that the following code is very basic, although it does include elitism.
MATLAB (an abbreviation of "MATrix LABoratory" [22]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
A comparison of the convergence of gradient descent with optimal step size (in green) and conjugate vector (in red) for minimizing a quadratic function associated with a given linear system. Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2).
The test functions used to evaluate the algorithms for MOP were taken from Deb, [4] Binh et al. [5] and Binh. [6] The software developed by Deb can be downloaded, [ 7 ] which implements the NSGA-II procedure with GAs, or the program posted on Internet, [ 8 ] which implements the NSGA-II procedure with ES.
Chebyshev nodes of both kinds from = to =.. For a given positive integer the Chebyshev nodes of the first kind in the open interval (,) are = (+), =, …,. These are the roots of the Chebyshev polynomials of the first kind with degree .
where is the gamma function, is the modified Bessel function of the second kind, and ρ and are positive parameters of the covariance. A Gaussian process with Matérn covariance is ⌈ ν ⌉ − 1 {\displaystyle \lceil \nu \rceil -1} times differentiable in the mean-square sense.
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If the objective function is concave (maximization problem), or convex (minimization problem) and the constraint set is convex, then the program is called convex and general methods from convex optimization can be used in most cases. If the objective function is quadratic and the constraints are linear, quadratic programming techniques are used.