Add to ORKGIn this paper we extend the results of Ermoliev, Norkin and Wets [8] and Ermoliev and Norkin [7] to the case of constrained discontinuous optimization problems. In contrast to [7] the attention is concentrated on the proof of general optimality conditions for problems with nonconvex feasible sets. Easily implementable random search technique is proposed
The paper is devoted to the study of a new notion of linear suboptimality in constrained mathematica...
Integrals of optimal values of random optimization problems depending on a finite dimensional parame...
AbstractThe conventional Lagrangian approach to solving constrained optimization problems leads to o...
In this paper stochastic programming techniques are adapted and further developed for applications t...
A deterministic global optimization method is developed for a class of discontinuous functions. McCo...
A class of stochastic optimization problems is analyzed that cannot be solved by deterministic and s...
A theoretical framework and a practical algorithm are presented to solve discontinuous piecewise lin...
We introduce a class of first-order methods for smooth constrained optimization that are based on an...
AbstractWith the integral approach to global optimization, a class of discontinuous penalty function...
We present an implementable algorithm for solving constrained optimization problems defined by funct...
To minimize discontinuous functions that arise in the context of systems with jumps, for example, we...
We introduce semismooth and semiconvex functions and discuss their properties with respect to nonsmo...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2014.This...
A stochastic algorithm for bound-constrained global optimization is described. The method can be ap...
Abstract. In this paper we analyze several concepts of solution to discontinuous ODEs in relation to...
The paper is devoted to the study of a new notion of linear suboptimality in constrained mathematica...
Integrals of optimal values of random optimization problems depending on a finite dimensional parame...
AbstractThe conventional Lagrangian approach to solving constrained optimization problems leads to o...
In this paper stochastic programming techniques are adapted and further developed for applications t...
A deterministic global optimization method is developed for a class of discontinuous functions. McCo...
A class of stochastic optimization problems is analyzed that cannot be solved by deterministic and s...
A theoretical framework and a practical algorithm are presented to solve discontinuous piecewise lin...
We introduce a class of first-order methods for smooth constrained optimization that are based on an...
AbstractWith the integral approach to global optimization, a class of discontinuous penalty function...
We present an implementable algorithm for solving constrained optimization problems defined by funct...
To minimize discontinuous functions that arise in the context of systems with jumps, for example, we...
We introduce semismooth and semiconvex functions and discuss their properties with respect to nonsmo...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2014.This...
A stochastic algorithm for bound-constrained global optimization is described. The method can be ap...
Abstract. In this paper we analyze several concepts of solution to discontinuous ODEs in relation to...
The paper is devoted to the study of a new notion of linear suboptimality in constrained mathematica...
Integrals of optimal values of random optimization problems depending on a finite dimensional parame...
AbstractThe conventional Lagrangian approach to solving constrained optimization problems leads to o...