This paper deals with approximate solutions of a nonsmooth semi-infinite programming multiple interval-valued objective functions. We first introduce four types quasi Pareto the considered problem by considering lower-upper interval order relation and then apply some advanced tools variational analysis generalized differentiation to establish necessary optimality conditions for these solutions....

Abstract In this paper, a class of E -differentiable vector optimization problems with both inequality and equality constraints is considered. The so-called mixed -dual problem defined for the considered constraints. Then, several -duality theorems are established under (generalized) V - -invexity hypotheses.

The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential Evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. Th...

Abstract In this paper, a class of stochastic vector variational inequality (SVVI) problems are considered. By employing the idea D-gap function, SVVI problem is reformulated as deterministic model, which an unconstrained expected residual minimization (UERM) problem, while it constrained in work Zhao et al. Then, properties objective function investigated and sample average approximation appro...

The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto–optimal solutions in a single run. Differential Evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. ...

We develop an algorithmic theory of convex optimization over discrete sets. Using a combination of algebraic and geometric tools we are able to provide polynomial time algorithms for solving broad classes of convex combinatorial optimization problems and convex integer programming problems in variable dimension. We discuss some of the many applications of this theory including to quadratic prog...