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1198. Vector exponential penalty E-function method for E-differentiable vector optimization problems

Invited abstract in session TB-37: Advances in Continuous Multiobjective Optimization, stream Multiobjective Optimization.

Tuesday, 10:30-12:00
Room: 33 (building: 306)

Authors (first author is the speaker)

1.	Najeeb Abdulaleem
	Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn

Abstract

In this paper, a new concept of generalized convexity is introduced for E-differentiable vector optimization problems. The concept of E-r-invexity is introduced as a generalization of the invexity notion. Further, a new vector exponential penalty E-function method for E-differentiable vector optimization problems is introduced. Furthermore, this work presents an investigation into two methods for solving multiobjective programming problems. First, it explores a sequence of vector penalized optimization problems utilizing a vector exponential penalty E-function. The convergence of this method is established. Next, it defines and analyzes the exactness property of a vector exact penalty E-function method within the context of the introduced vector exponential penalty E-function method. Conditions are provided to ensure the equivalence of sets of (weak) E-Pareto solutions between the original E-differentiable optimization problem and the associated vector E-penalized optimization problem using the vector exact exponential penalty E-function. This equivalence is established for E-differentiable vector optimization problems involving E-r-invex functions.

Keywords

• Mathematical Programming
• Programming, Multi-Objective
• Programming, Nonlinear

Status: accepted

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