Add to ORKGA depth-first analog to the Lipschitz based Piyavskii-Shubert global maximization algorithm is presented. To within any given tolerance, the algorithm is shown to return a global maximum and maximizer for a uni-variate Lipschitz continuous function. This result is extended to a broader class of uni-variate functions. Empirical comparisons of Piyavskii-Shubert with several variations of the new algorithm are made
We consider the problem of maximizing a non-concave Lipschitz multivariate function over a compact d...
In this work, we present a new deterministic partition-based Global Optimization (GO) algorithm that...
Global optimization methods based on Lipschitz bounds have been analyzed and applied widely to solve...
The global optimisation problem has received much attention in the past twenty-five years. The probl...
The global optimization problem min f(x), x in S with S=[a,b], a, b in Rn and f(x) satisfying the L...
This paper deals with two kinds of the one-dimensional global optimization problem over a closed fin...
A branch and bound algorithm for global optimization is proposed, where the maximum of an upper boun...
This paper is devoted to the study of partition-based deterministic algorithms for global optimizati...
AbstractA new algorithm for full global optimization of a Lipschitzian function over an arbitrary bo...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
We consider the problem of maximizing a non-concave Lipschitz multivariate function over a compact d...
AbstractA family of deterministic algorithms is introduced, designed to solve the global optimisatio...
Methods of Lipschitz optimization allow one to find and confirm the global minimum of multivariate L...
This paper introduces an innovative extension of the DIRECT algorithm specifically designed to solve...
We consider a family of function classes which allow functions with several minima and which deman...
We consider the problem of maximizing a non-concave Lipschitz multivariate function over a compact d...
In this work, we present a new deterministic partition-based Global Optimization (GO) algorithm that...
Global optimization methods based on Lipschitz bounds have been analyzed and applied widely to solve...
The global optimisation problem has received much attention in the past twenty-five years. The probl...
The global optimization problem min f(x), x in S with S=[a,b], a, b in Rn and f(x) satisfying the L...
This paper deals with two kinds of the one-dimensional global optimization problem over a closed fin...
A branch and bound algorithm for global optimization is proposed, where the maximum of an upper boun...
This paper is devoted to the study of partition-based deterministic algorithms for global optimizati...
AbstractA new algorithm for full global optimization of a Lipschitzian function over an arbitrary bo...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
We consider the problem of maximizing a non-concave Lipschitz multivariate function over a compact d...
AbstractA family of deterministic algorithms is introduced, designed to solve the global optimisatio...
Methods of Lipschitz optimization allow one to find and confirm the global minimum of multivariate L...
This paper introduces an innovative extension of the DIRECT algorithm specifically designed to solve...
We consider a family of function classes which allow functions with several minima and which deman...
We consider the problem of maximizing a non-concave Lipschitz multivariate function over a compact d...
In this work, we present a new deterministic partition-based Global Optimization (GO) algorithm that...
Global optimization methods based on Lipschitz bounds have been analyzed and applied widely to solve...