Redundancy Optimization of Finite-Dimensional Structures: Concept and Derivative-Free Algorithm

Derivative-free optimization methods for finite minimax problems

Derivative-free optimization focuses on designing methods to solve optimization problems without the analytical knowledge of the function. In this paper we consider the problem of designing derivative-free methods for finite minimax problems: minx maxi=1,2,...N{fi(x)}. In order to solve the problem efficiently, we seek to exploit the smooth substructure within the problem. Using ideas developed...

A Derivative-Free Algorithm for Linearly Constrained Finite Minimax Problems

In this paper we propose a new derivative-free algorithm for linearly constrained finite minimax problems. Due to the nonsmoothness of this class of problems, standard derivative-free algorithms can only locate points which satisfy weak necessary optimality conditions. In this work we define a new derivative-free algorithm which is globally convergent toward standard stationary points of the fi...

Derivative-free Efficient Global Optimization on High-dimensional Simplex

In this paper, we develop a novel derivative-free deterministic greedy algorithm for global optimization of any objective function of parameters belonging to a unit-simplex. Main principle of the proposed algorithm is making jumps of varying step-sizes within the simplex parameter space and searching for the best direction to move in a greedy manner. Unlike most of the other existing methods of...

Derivative Free Optimization

Derivative-Free Optimization

In many engineering applications it is common to find optimization problems where the cost function and/or constraints require complex simulations. Though it is often, but not always, theoretically possible in these cases to extract derivative information efficiently, the associated implementation procedures are typically non-trivial and time-consuming (e.g., adjoint-based methodologies). Deriv...