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Symmetry
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Symmetry in Optimization Algorithms and Applications
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Symmetry in Optimization Algorithms and Applications

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

Deadline for manuscript submissions: 31 August 2025 | Viewed by 533

Special Issue Editor

Prof. Dr. Adrián González

E-Mail Website
Guest Editor
Departamento de Ingeniería Electro-Fotónica, Universidad de Guadalajara (CUCEI), Blvd. Marcelino García Barragán #1421, Guadalajara 44430, Mexico
Interests: evolutionary algorithms

Special Issue Information

Dear Colleagues,

This Special Issue, "Symmetry in Optimization Algorithms and Applications", examines how symmetry, present in many optimization problems, impacts the efficiency and performance of algorithms. It explores methods to identify and leverage symmetries to simplify problems, reduce search spaces, and speed up convergence. Practical applications are discussed in fields such as mathematical programming, artificial intelligence, and combinatorial optimization. The Issue will also address challenges such as breaking unnecessary symmetries to avoid redundant solutions and ensuring algorithm robustness in real-world scenarios.  

Prof. Dr. Adrián González
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • symmetry
  • optimization algorithms
  • problem simplification
  • search space reduction
  • algorithm efficiency
  • symmetry breaking
  • mathematical programming
  • combinatorial optimization
  • convergence acceleration

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Published Papers (1 paper)

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Research

26 pages, 2942 KiB  
Article
An Improved Whale Migration Algorithm for Global Optimization of Collaborative Symmetric Balanced Learning and Cloud Task Scheduling
by Honggan Lu, Shenghao Cheng and Xinsheng Zhang
Symmetry 2025, 17(6), 841; https://doi.org/10.3390/sym17060841 - 27 May 2025
Viewed by 217
Abstract
In today’s complex and ever-changing fields of science and engineering, intelligent optimization algorithms have become a key tool. However, the complexity of the problem itself often poses a severe challenge to the performance of the algorithm. The whale migration algorithm stands out among [...] Read more.
In today’s complex and ever-changing fields of science and engineering, intelligent optimization algorithms have become a key tool. However, the complexity of the problem itself often poses a severe challenge to the performance of the algorithm. The whale migration algorithm stands out among numerous optimization algorithms with its simple and efficient implementation and has received extensive attention. However, when confronted with complex issues such as global optimization and task scheduling, it still exposes some deficiencies including low initial population symmetry (i.e., poor distribution uniformity and insufficient balance between exploration and exploitation in iterative processes). The development ability of the algorithm is relatively weak, making it difficult to conduct an effective search and optimization in the complex problem space. The task scheduling strategy is not optimized enough, which affects the application of the algorithm in actual task scheduling scenarios. To overcome these challenges, this paper proposes an improved whale migration algorithm. Based on inheriting the original advantages of the whale migration algorithm, this algorithm effectively solves the above problems by introducing a new mechanism. The CEC2021 test function set was selected, and the effectiveness of the proposed strategy was verified through point-by-point ablation experiments. The algorithm was comprehensively verified through the CEC2022 test problem set, verifying the effectiveness and robustness of the algorithm in global optimization problems. Furthermore, the proposed algorithm was tested for cloud task scheduling problems of different scales. The experimental results show that the proposed algorithm can reduce the total scheduling cost by about 9% or more. Full article
(This article belongs to the Special Issue Symmetry in Optimization Algorithms and Applications)
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