Symmetry/Asymmetry in Optimization Algorithms and Systems Control

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 30 March 2026 | Viewed by 724

Special Issue Editors

School of Management, Guizhou University, Guizhou 550025, China
Interests: logistics system modeling and optimization; unmanned systems and intelligent scheduling; multi-objective optimization; intelligent simulation and modeling

E-Mail Website
Guest Editor
School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: unmanned systems optimization; control and applications of multi-agent systems; intelligent optimization algorithms and simulation

Special Issue Information

Dear Colleagues,

Optimization algorithms and systems control are fundamental to solving complex decision-making problems in various domains, including logistics, supply chain management, unmanned systems, and intelligent scheduling. Symmetry in optimization can lead to elegant and computationally efficient solutions, enabling better problem decomposition, solution space reduction, and algorithmic robustness. However, real-world systems often exhibit asymmetries due to uncertainties, dynamic environments, and heterogeneous resource constraints, necessitating adaptive and asymmetric optimization strategies.

This Special Issue aims to explore the role of symmetry and asymmetry in optimization algorithms and systems control, emphasizing the impact on computational efficiency, decision-making accuracy, and practical applicability. We welcome contributions that investigate novel theoretical advancements, algorithmic innovations, and real-world applications of symmetric and asymmetric optimization in logistics, autonomous systems, multi-objective decision-making, and intelligent modeling. Topics that are invited for submission include (but are not limited to):

  • Symmetric and asymmetric optimization
  • Convex and non-convex optimization
  • Multi-objective optimization
  • Intelligent scheduling and routing optimization
  • Metaheuristics and hybrid algorithms
  • Data-Driven Optimization
  • Machine Learning and Data Science
  • Unmanned systems optimization
  • Logistics and supply chain control
  • Dynamic resource allocation

We look forward to receiving your contributions.

Dr. Yuhe Shi
Dr. Yuanyuan Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • optimization algorithm
  • systems control
  • autonomous system
  • multi-objective decision-making

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 3357 KB  
Article
Time-Varying Current Estimation Method for SINS/DVL Integrated Navigation Based on Augmented Observation Algorithm
by Xin Chen, Hongwei Bian, Fangneng Li, Rongying Wang, Yaojin Hu and Jingshu Li
Symmetry 2025, 17(11), 1881; https://doi.org/10.3390/sym17111881 - 5 Nov 2025
Viewed by 451
Abstract
To address the problem of the bottom velocity being directly affected by the time-varying ocean currents when DVL operates in the water observation mode, it cannot be directly used for combined SINS/DVL navigation. Existing methods generally approximate small-scale, short-term currents as constant; however, [...] Read more.
To address the problem of the bottom velocity being directly affected by the time-varying ocean currents when DVL operates in the water observation mode, it cannot be directly used for combined SINS/DVL navigation. Existing methods generally approximate small-scale, short-term currents as constant; however, this assumption is inconsistent with reality over longer durations. When the conventional Kalman filter (KF) algorithm incorporates currents into the state vector, their velocities become entangled with the SINS errors, limiting estimation accuracy. This paper proposes an augmented observation algorithm (AOA) that achieves error decoupling by enhancing DVL observation and deriving the observable current velocity equation without needing external observation information. This approach effectively estimates time-varying currents. The results from simulations and shipboard tests show that, compared to the reference algorithm (Augmented Observation Quantity Filtering algorithm (AOQ)), the proposed AOA significantly decreases the root mean square error (RMSE) of time-varying current velocity estimation by more than 67%. Additionally, the RMSE of the positioning accuracy of the combined SINS/DVL navigation is improved by over 68%. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Optimization Algorithms and Systems Control)
Show Figures

Figure 1

Back to TopTop