Next Article in Journal
A Unified Framework for the Upper and Lower Discretizations of Fuzzy Implications
Previous Article in Journal
Investigating Uniform Stability of Fractional-Order Complex-Valued Stochastic Neural Networks with Impulses via a Direct Method
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Using the Embedding Theorem to Solve Interval-Valued Optimization Problems

Department of Mathematics, National Kaohsiung Normal University, Kaohsiung 824, Taiwan
Axioms 2026, 15(1), 18; https://doi.org/10.3390/axioms15010018 (registering DOI)
Submission received: 31 October 2025 / Revised: 13 December 2025 / Accepted: 25 December 2025 / Published: 26 December 2025
(This article belongs to the Special Issue Recent Advances in Mathematical Optimization and Related Topics)

Abstract

The space of all bounded closed intervals cannot form a vector space because the concept of an additive inverse cannot be considered. Therefore, this paper presents an embedding theorem to show that the space of all bounded closed intervals can be embedded into a Banach space. In this case, the partial orders among the space of all bounded closed intervals can be proposed via the embedding theorem by considering the ordering cones in that Banach space. After a partial order is introduced in the interval-valued optimization problem, the solution concepts of interval-valued optimization problem can be naturally defined. On the other hand, using the embedding theorem, an auxiliary vector optimization problem is introduced such that solving the original interval-valued optimization problem is equivalent to solving the auxiliary vector optimization problem. The technique of scalarization is proposed to solve the auxiliary vector optimization problem. Three practical ordering cones are considered to study the linear type of interval-valued optimization problem for the purpose of presenting practical applications.
Keywords: embedding theorem; minimal element; ordering cone; partial order; scalarization embedding theorem; minimal element; ordering cone; partial order; scalarization

Share and Cite

MDPI and ACS Style

Wu, H.-C. Using the Embedding Theorem to Solve Interval-Valued Optimization Problems. Axioms 2026, 15, 18. https://doi.org/10.3390/axioms15010018

AMA Style

Wu H-C. Using the Embedding Theorem to Solve Interval-Valued Optimization Problems. Axioms. 2026; 15(1):18. https://doi.org/10.3390/axioms15010018

Chicago/Turabian Style

Wu, Hsien-Chung. 2026. "Using the Embedding Theorem to Solve Interval-Valued Optimization Problems" Axioms 15, no. 1: 18. https://doi.org/10.3390/axioms15010018

APA Style

Wu, H.-C. (2026). Using the Embedding Theorem to Solve Interval-Valued Optimization Problems. Axioms, 15(1), 18. https://doi.org/10.3390/axioms15010018

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop