Justification of Necessary Optimality Conditions for Certain Integral Functionals

1987 ◽  
pp. 207-218
Author(s):  
Thomas I. Seidman
Keyword(s):  
Optimality Conditions ◽  
Necessary Optimality Conditions ◽  
Integral Functionals

scholarly journals On a Class of Isoperimetric Constrained Controlled Optimization Problems

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 112
Author(s):  
Savin Treanţă
Keyword(s):  
Boundary Conditions ◽  
Control Problem ◽  
Optimality Conditions ◽  
Optimization Problems ◽  
Necessary Optimality Conditions ◽  
Control Problems ◽  
Integral Functionals ◽  
Curvilinear Integral ◽  
The One ◽  
Theoretical Results

In this paper, we investigate the Lagrange dynamics generated by a class of isoperimetric constrained controlled optimization problems involving second-order partial derivatives and boundary conditions. More precisely, we derive necessary optimality conditions for the considered class of variational control problems governed by path-independent curvilinear integral functionals. Moreover, the theoretical results presented in the paper are accompanied by an illustrative example. Furthermore, an algorithm is proposed to emphasize the steps to be followed to solve a control problem such as the one studied in this paper.

scholarly journals Robust Necessary Optimality Conditions for Nondifferentiable Complex Fractional Programming with Uncertain Data

2021 ◽  
Vol 189 (1) ◽  
pp. 221-243
Author(s):  
Jiawei Chen ◽  
Suliman Al-Homidan ◽  
Qamrul Hasan Ansari ◽  
Jun Li ◽  
Yibing Lv
Keyword(s):  
Optimality Conditions ◽  
Fractional Programming ◽  
Uncertain Data ◽  
Necessary Optimality Conditions

A concept of inner prederivative for set-valued mappings and its applications

2018 ◽  
Vol 24 (3) ◽  
pp. 1059-1074
Author(s):  
Michel H. Geoffroy ◽  
Yvesner Marcelin
Keyword(s):  
Optimality Conditions ◽  
Necessary Optimality Conditions ◽  
Welfare Economics ◽  
Inverse Mapping ◽  
First Order ◽  
Inverse Mapping Theorem ◽  
Homogeneous Set ◽  
Optimal Allocations ◽  
Variational Perturbations ◽  
Set Valued Mappings

We introduce a class of positively homogeneous set-valued mappings, called inner prederivatives, serving as first order approximants to set-valued mappings. We prove an inverse mapping theorem involving such prederivatives and study their stability with respect to variational perturbations. Then, taking advantage of their properties we establish necessary optimality conditions for the existence of several kind of minimizers in set-valued optimization. As an application of these last results, we consider the problem of finding optimal allocations in welfare economics. Finally, to emphasize the interest of our approach, we compare the notion of inner prederivative to the related concepts of set-valued differentiation commonly used in the literature.

scholarly journals Minimum Principle-Type Necessary Optimality Conditions in Scalar and Vector Optimization. An Account

2017 ◽  
Vol 9 (4) ◽  
pp. 168
Author(s):  
Giorgio Giorgi
Keyword(s):  
Optimality Conditions ◽  
Vector Optimization ◽  
Optimization Problems ◽  
Minimum Principle ◽  
Necessary Optimality Conditions ◽  
Equality Constraints ◽  
Vector Optimization Problems ◽  
Scalar Optimization ◽  
Scalar And Vector Optimization

We take into condideration necessary optimality conditions of minimum principle-type, that is for optimization problems having, besides the usual inequality and/or equality constraints, a set constraint. The first part pf the paper is concerned with scalar optimization problems; the second part of the paper deals with vector optimization problems.

scholarly journals Numerical Algorithms For State-Linear Optimal Impulsive Control Problems Based On Feedback Necessary Optimality Conditions

2020 ◽  
pp. 152-158
Author(s):  
Stepan Sorokin ◽  
Maxim Staritsyn
Keyword(s):  
Optimality Conditions ◽  
Impulsive Control ◽  
Numerical Algorithms ◽  
Necessary Optimality Conditions ◽  
Maximum Principles ◽  
Control Problems ◽  
Impulsive Systems ◽  
Feedback Controls ◽  
Non Local ◽  
Optimal Impulsive Control

We propose and compare three numeric algorithms for optimal control of state-linear impulsive systems. The algorithms rely on the standard transformation of impulsive control problems through the discontinuous time rescaling, and the so-called “feedback”, direct and dual, maximum principles. The feedback maximum principles are variational necessary optimality conditions operating with feedback controls, which are designed through the usual constructions of the Pontryagin’s Maximum Principle (PMP); though these optimality conditions are formulated completely in the formalism of PMP, they essentially strengthen it. All the algorithms are non-local in the sense that they are aimed at improving non-optimal extrema of PMP (local minima), and, therefore, show the potential of global optimization.

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