Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.9
2.7
Journals
Symmetry
Special Issues
Symmetry in Computing Algorithms and Applications
share announcement

Symmetry in Computing Algorithms and Applications

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

Deadline for manuscript submissions: 28 February 2025 | Viewed by 2286

Special Issue Editors

Dr. Lei Yue

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510000, China
Interests: intelligent manufacturing system; digital modeling and simulation; digital twin in manufacturing operations; production line balancing; smart optimization algorithms
Dr. Jinhua Zhang

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China
Interests: mathematical modeling; adaptive robust control; vehicle dynamics

Special Issue Information

Dear Colleagues,

Symmetry plays a crucial role in computing algorithms and their applications, contributing to efficiency, aesthetics, and problem-solving in various domains. In algorithm design, symmetry often leads to elegant solutions that simplify complex problems, since it can help us find patterns and regularities in data and improve the efficiency and accuracy of algorithms. For example, sorting algorithms like Quicksort and Mergesort exploit symmetry to divide and conquer, reducing time complexity. Symmetric data structures, such as binary trees and balanced search trees, ensure efficient data retrieval and insertion. In addition to sorting algorithms, symmetry also appears in other types of algorithms. For example, some machine learning algorithms use symmetry to find patterns in data and classify or cluster similar objects. Symmetry can also help us find regularities in regular expressions and improve the efficiency of pattern-matching algorithms. Moreover, symmetry finds applications in artificial intelligence and machine learning, where it assists in feature extraction, dimensionality reduction, and data preprocessing. Recognizing symmetries in datasets can improve classification accuracy and reduce computational complexity. In summary, symmetry is a powerful concept in computing, with widespread applications across algorithms and various fields. In this Special Issue, we invite submissions focusing on novel models that can predict, detect, and adapt to symmetric solutions in complex mathematic programming. We particularly encourage research that explores the practical applications of these models and algorithms in solving industrial problems.

The focus of this Special Issue is to continue to advance research on topics relating to the Symmetry in Computing Algorithms and Applications. Topics that are invited for submission include (but are not limited to):

  • Symmetries of complex manufacturing systems;
  • Artificial intelligence (AI) in production scheduling;
  • Fuzzy computing;
  • Data analytics for manufacturing;
  • Cloud computing for manufacturing;
  • Predictive maintenance;
  • Real-time monitoring and control;
  • Supply chain optimization;
  • Computing applications;
  • Smart decision support for industry.

Dr. Lei Yue
Dr. Jinhua 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 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

  • symmetries of complex manufacturing systems
  • Artificial Intelligence (AI) in production scheduling
  • fuzzy computing
  • data analytics for manufacturing
  • cloud computing for manufacturing
  • predictive maintenance
  • real-time monitoring and control
  • supply chain optimization
  • computing applications
  • smart decision support for industry

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 1108 KiB  
Article
Particle Swarm Optimization Algorithm Using Velocity Pausing and Adaptive Strategy
by Kezong Tang and Chengjian Meng
Symmetry 2024, 16(6), 661; https://doi.org/10.3390/sym16060661 - 27 May 2024
Viewed by 285
Abstract
Particle swarm optimization (PSO) as a swarm intelligence-based optimization algorithm has been widely applied to solve various real-world optimization problems. However, traditional PSO algorithms encounter issues such as premature convergence and an imbalance between global exploration and local exploitation capabilities when dealing with [...] Read more.
Particle swarm optimization (PSO) as a swarm intelligence-based optimization algorithm has been widely applied to solve various real-world optimization problems. However, traditional PSO algorithms encounter issues such as premature convergence and an imbalance between global exploration and local exploitation capabilities when dealing with complex optimization tasks. To address these shortcomings, an enhanced PSO algorithm incorporating velocity pausing and adaptive strategies is proposed. By leveraging the search characteristics of velocity pausing and the terminal replacement mechanism, the problem of premature convergence inherent in standard PSO algorithms is mitigated. The algorithm further refines and controls the search space of the particle swarm through time-varying inertia coefficients, symmetric cooperative swarms concepts, and adaptive strategies, balancing global search and local exploitation. The performance of VASPSO was validated on 29 standard functions from Cec2017, comparing it against five PSO variants and seven swarm intelligence algorithms. Experimental results demonstrate that VASPSO exhibits considerable competitiveness when compared with 12 algorithms. The relevant code can be found on our project homepage. Full article
(This article belongs to the Special Issue Symmetry in Computing Algorithms and Applications)
►▼ Show Figures

Figure 1

28 pages, 1809 KiB  
Article
An Adaptive Search Algorithm for Multiplicity Dynamic Flexible Job Shop Scheduling with New Order Arrivals
by Linshan Ding, Zailin Guan, Dan Luo, Mudassar Rauf and Weikang Fang
Symmetry 2024, 16(6), 641; https://doi.org/10.3390/sym16060641 - 22 May 2024
Viewed by 458
Abstract
In today’s customer-centric economy, the demand for personalized products has compelled corporations to develop manufacturing processes that are more flexible, efficient, and cost-effective. Flexible job shops offer organizations the agility and cost-efficiency that traditional manufacturing processes lack. However, the dynamics of modern manufacturing, [...] Read more.
In today’s customer-centric economy, the demand for personalized products has compelled corporations to develop manufacturing processes that are more flexible, efficient, and cost-effective. Flexible job shops offer organizations the agility and cost-efficiency that traditional manufacturing processes lack. However, the dynamics of modern manufacturing, including machine breakdown and new order arrivals, introduce unpredictability and complexity. This study investigates the multiplicity dynamic flexible job shop scheduling problem (MDFJSP) with new order arrivals. To address this problem, we incorporate the fluid model to propose a fluid randomized adaptive search (FRAS) algorithm, comprising a construction phase and a local search phase. Firstly, in the construction phase, a fluid construction heuristic with an online fluid dynamic tracking policy generates high-quality initial solutions. Secondly, in the local search phase, we employ an improved tabu search procedure to enhance search efficiency in the solution space, incorporating symmetry considerations. The results of the numerical experiments demonstrate the superior effectiveness of the FRAS algorithm in solving the MDFJSP when compared to other algorithms. Specifically, the proposed algorithm demonstrates a superior quality of solution relative to existing algorithms, with an average improvement of 29.90%; and exhibits an acceleration in solution speed, with an average increase of 1.95%. Full article
(This article belongs to the Special Issue Symmetry in Computing Algorithms and Applications)
►▼ Show Figures

Figure 1

21 pages, 2144 KiB  
Article
Scheduling Optimization of Compound Operations in Autonomous Vehicle Storage and Retrieval System
by Lili Xu, Jiansha Lu and Yan Zhan
Symmetry 2024, 16(2), 168; https://doi.org/10.3390/sym16020168 - 31 Jan 2024
Viewed by 766
Abstract
The increasing demand for storing various types of goods has led to a raise in the need for storage capacity in warehousing systems. Autonomous vehicle storage and retrieval systems (AVS/RSs) offer high flexibility by allowing different configurations to meet different storage requirements. The [...] Read more.
The increasing demand for storing various types of goods has led to a raise in the need for storage capacity in warehousing systems. Autonomous vehicle storage and retrieval systems (AVS/RSs) offer high flexibility by allowing different configurations to meet different storage requirements. The system mainly completes operations through elevators and multiple rail-guided vehicles (RGVs). This paper focuses on the scheduling optimization of compound operations in the AVS/RS to improve system performance. Compound operations involve the coordinated execution of both single-command and double-command operations. A mathematical model with compound operations was proposed and effectively decomposed into a horizontal component for RGVs and a vertical counterpart for the elevator, which can represent the operations of one elevator cooperating with multiple RGVs. The goal of this model was to minimize the makespan for compound operations and to determine the optimal operation sequence and path for RGVs. An improved discrete particle swarm optimization (DPSO) algorithm called AGDPSO was proposed to solve the model. The algorithm combines DPSO and a genetic algorithm in an adaptive manner to prevent the algorithm from falling into local optima and relying solely on the initial solution. Through rigorous optimization, optimal parameters for the algorithm were identified. When assessing the performance of our improved algorithm against various counterparts, considering different task durations and racking configurations, our results showed that AGDPSO outperformed the alternatives, proving its effectiveness in enhancing system efficiency for the model. The findings of this study not only contribute to the optimization of AVS/RS but also offer valuable insights for designing more efficient warehouses. By streamlining scheduling, improving operations, and leveraging advanced optimization techniques, we can create a more robust and effective storage and retrieval system. Full article
(This article belongs to the Special Issue Symmetry in Computing Algorithms and Applications)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop