A well-known example of global optimization that provides solutions within fixed error limits is optimization of functions with a known Lipschitz constant. In many real-life problems this constant is unknown. To address that, we propose a novel method called Pareto Lipschitzian Optimization (PLO) that provides solutions within fixed error limits for functions with unknown Lipschitz constants.In the proposed approach, a set of all unknown Lipschitz constants is regarded as multiple criteria using the concept of Pareto Optimality (PO)
The global optimization problem min f(x), x in S with S=[a,b], a, b in Rn and f(x) satisfying the L...
We consider the parametric minimization problem with a Lipschitz objective function. We propose an a...
This paper is devoted to the study of partition-based deterministic algorithms for global optimizati...
A well-known example of global optimization that provides solutions within fixed error limits is opt...
A well-known example of global optimization that provides solutions within fixed error limits is opt...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
AbstractA new algorithm for full global optimization of a Lipschitzian function over an arbitrary bo...
In this thesis, Direct (DIviding RECTangles) type algorithms based on Lipschitz objective function m...
We consider a family of function classes which allow functions with several minima and which deman...
The paper discusses how the used norm and corresponding Lipschitz constant influence the speed of al...
This work addresses the sequential optimization of an unknown and potentially nonconvex function ove...
In this work, we present a new deterministic partition-based Global Optimization (GO) algorithm that...
Abstract. Optimality conditions are established in terms of Lagrange– Kuhn–Tucker multipliers for mu...
This paper introduces an innovative extension of the DIRECT algorithm specifically designed 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...
We consider the parametric minimization problem with a Lipschitz objective function. We propose an a...
This paper is devoted to the study of partition-based deterministic algorithms for global optimizati...
A well-known example of global optimization that provides solutions within fixed error limits is opt...
A well-known example of global optimization that provides solutions within fixed error limits is opt...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
AbstractA new algorithm for full global optimization of a Lipschitzian function over an arbitrary bo...
In this thesis, Direct (DIviding RECTangles) type algorithms based on Lipschitz objective function m...
We consider a family of function classes which allow functions with several minima and which deman...
The paper discusses how the used norm and corresponding Lipschitz constant influence the speed of al...
This work addresses the sequential optimization of an unknown and potentially nonconvex function ove...
In this work, we present a new deterministic partition-based Global Optimization (GO) algorithm that...
Abstract. Optimality conditions are established in terms of Lagrange– Kuhn–Tucker multipliers for mu...
This paper introduces an innovative extension of the DIRECT algorithm specifically designed 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...
We consider the parametric minimization problem with a Lipschitz objective function. We propose an a...
This paper is devoted to the study of partition-based deterministic algorithms for global optimizati...