This outstanding text for graduate students and researchers proposes improvements to existing algorithms, extends their related mathematical theories, and offers details on new algorithms for approximating local and global minima. None of the algorithms requires an evaluation of derivatives; all depend entirely on sequential function evaluation, a highly practical scenario in the frequent event of difficult-to-evaluate derivatives.Topics include the use of successive interpolation for finding simple zeros of a function and its derivatives; an algorithm with guaranteed convergence for findin
An efficient and rapid heuristic local search method is dealt with, which can be applied for a wide ...
This book begins with a concentrated introduction into deterministic global optimization and moves f...
In this work, we propose a new globally convergent derivative-free algorithm for the minimization of...
Existing algorithms are examined, with particular attention given to their merits and defects, in or...
We develop a framework for a class of derivative-free algorithms for the least-squares minimization ...
We consider some algorithms for unconstrained minimization without derivatives that form linear or q...
Quadratic approximations to the objective function provide a way of estimating first and second deri...
Abstract: Let the least value of the function F (x), x∈Rn, be required, where n ≥ 2. If the gradient...
The problem of finding a local or a global minimum of a real function on a set S, a subset of Rn, p...
In this paper, acceptability criteria for the stepsize and global convergence conditions are establi...
Abstract. This paper presents a general approach that combines global search strategies with local s...
An unconstrained minimization method which is based on Powell's derivative free method is prese...
A simple derivative free optimization method is presented. Some examples are provided showing the sp...
The problem of finding a local or a global minimum of a real function on a set S, a subset of Rn, p...
There exists many applications with so-called costly problems, which means that the objective functi...
An efficient and rapid heuristic local search method is dealt with, which can be applied for a wide ...
This book begins with a concentrated introduction into deterministic global optimization and moves f...
In this work, we propose a new globally convergent derivative-free algorithm for the minimization of...
Existing algorithms are examined, with particular attention given to their merits and defects, in or...
We develop a framework for a class of derivative-free algorithms for the least-squares minimization ...
We consider some algorithms for unconstrained minimization without derivatives that form linear or q...
Quadratic approximations to the objective function provide a way of estimating first and second deri...
Abstract: Let the least value of the function F (x), x∈Rn, be required, where n ≥ 2. If the gradient...
The problem of finding a local or a global minimum of a real function on a set S, a subset of Rn, p...
In this paper, acceptability criteria for the stepsize and global convergence conditions are establi...
Abstract. This paper presents a general approach that combines global search strategies with local s...
An unconstrained minimization method which is based on Powell's derivative free method is prese...
A simple derivative free optimization method is presented. Some examples are provided showing the sp...
The problem of finding a local or a global minimum of a real function on a set S, a subset of Rn, p...
There exists many applications with so-called costly problems, which means that the objective functi...
An efficient and rapid heuristic local search method is dealt with, which can be applied for a wide ...
This book begins with a concentrated introduction into deterministic global optimization and moves f...
In this work, we propose a new globally convergent derivative-free algorithm for the minimization of...