Generalized-Hukuhara penalty method for optimization problem with interval-valued functions and its application in interval-valued portfolio optimization problems

Amit Kumar Debnath; Debdas Ghosh

doi:10.1016/j.orl.2022.08.010

ScienceGate Book Chapters

JOURNAL ARTICLE

Generalized-Hukuhara penalty method for optimization problem with interval-valued functions and its application in interval-valued portfolio optimization problems

Amit Kumar Debnath Debdas Ghosh

Year: 2022 Journal: Operations Research Letters Vol: 50 (5)Pages: 602-609 Publisher: Elsevier BV

DOI: 10.1016/j.orl.2022.08.010

Get Full-Text PDF Get Analytical Report

Keywords:

Interval (graph theory) Penalty method Mathematical optimization Optimization problem Mathematics Interval arithmetic Portfolio Function (biology) Portfolio optimization Computer science

Metrics

Cited By

3.34

FWCI (Field Weighted Citation Impact)

Refs

0.87

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Fuzzy Systems and Optimization

Physical Sciences → Mathematics → Statistics and Probability

Risk and Portfolio Optimization

Social Sciences → Decision Sciences → Management Science and Operations Research

Optimization and Mathematical Programming

Physical Sciences → Engineering → Control and Systems Engineering

Generalized-Hukuhara penalty method for optimization problem with interval-valued functions and its application in interval-valued portfolio optimization problems

Metrics

Citation History

Topics

Related Documents

Generalized-Hukuhara subgradient and its application in optimization problem with interval-valued functions

Generalized Hukuhara Gâteaux and Fréchet derivatives of interval-valued functions and their application in optimization with interval-valued functions

On interval-valued optimization problems with generalized invex functions

A generalization of generalized Hukuhara Newton's method for interval-valued multiobjective optimization problems

Generalized Hukuhara Hadamard derivative of interval-valued functions and its applications to interval optimization