Optimality conditions and duality for multiobjective semi-infinite programming with data uncertainty via Mordukhovich subdifferential

Abstract

Based on the notation of Mordukhovich subdifferential in [27], we propose some of new concepts of convexity to establish optimality conditions for quasi ?-solutions for nonlinear semi-infinite optimization problems with data uncertainty in constraints. Moreover, some examples are given to illustrate the obtained results.

On approximate positively properly efficient solutions in nonsmooth semi-infinite multiobjective optimization problems with data uncertainty

“…Optimality conditions and duality theorems for approximate solutions of a multiobjective optimization problems were studied in [29,30,31] and optimality conditions/duality theorems/saddle point theorems for approximate solutions of optimization problems with infinite constraints were given in [32,33,34,35,36,37,38,39]. On the other hand, optimality conditions/duality theorems for approximate solutions of robust optimization problems with infinite constraints were obtained in [40,41,42]. However, to the best of our knowledge, up to now, there is no paper devoted to ε-quasi positively properly efficient solutions of semi-infinite multiobjective optimization problems with data uncertainty.…”

Optimality Conditions and Duality for MultiobjectiveSemi-infinite Optimization Problems with SwitchingConstraints on Hadamard Manifolds

“…In recent times, several real life problems appearing in various őelds of science and engineering, such as, digital őlter design [29], air pollution control [59], lapidary cutting problems [62], statistical design [18], robotic trajectory planning [58], eigenvalue computations [18], production planning [60], have been modelled as (SIPs). For more details and updated survey on semi-inőnite programming, we refer to [14,34,41] and the references cited therein.…”

A neutrosophical model for optimal sustainable closed-loop supply chain network with considering inflation and carbon emission policies

“…Therefore, some important parameters such as customer demands are completely unclear and appropriate planning to deal with this uncertainty seems necessary. In this connection, studies on the design of a stable CLSC under uncertainty have attracted the attention of researchers, which can be referred to (De et al, 2020;Alegoz et al, 2020;Pham, 2021). In a stable CLSC, financial factors are important because they have a greater impact on supply, production, distribution, and recycling.…”