Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)

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Multi-Objective to Dynamic Single-Objective Based on Improved Ant Colony Algorithm

Authors
Liuxin Liu1, *
1Northeast Normal University, Changchun, China
*Corresponding author. Email: 2021012994@nenu.edu.cn
Corresponding Author
Liuxin Liu
Available Online 20 February 2026.
DOI
10.2991/978-94-6463-992-6_3How to use a DOI?
Keywords
multi-objective; portfolio; improved ant colony algorithm
Abstract

To solve multi-objective portfolio problems, it is often necessary to directly calculate the Pareto Frontier to obtain all the optimal solutions. However, when the number of decision objectives increases, it is easy to have problems such as the huge dimension of the solution space that cannot produce results, and the image cannot be drawn. we propose dynamically linearly weighting the decision objectives in the original problem and transforming them into a dynamic single-objective model. This allows for the adjustment of unfixed weights. This paper construct an improved ant colony algorithm called UACO to highlight the benefits of single-objective optimization. To verify the applicability of this method, a common bi-objective portfolio optimization problem can be selected for calculation, and the data fitting results can be compared with a Pareto Frontier obtained by another conventional algorithm.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
20 February 2026
ISBN
978-94-6463-992-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-992-6_3How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Liuxin Liu
PY  - 2026
DA  - 2026/02/20
TI  - Multi-Objective to Dynamic Single-Objective Based on Improved Ant Colony Algorithm
BT  - Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)
PB  - Atlantis Press
SP  - 12
EP  - 21
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-992-6_3
DO  - 10.2991/978-94-6463-992-6_3
ID  - Liu2026
ER  -