Symmetry and Asymmetry in Intelligent Control and Computing

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

Deadline for manuscript submissions: 28 February 2026 | Viewed by 217

Special Issue Editors


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Guest Editor
College of Cyber Security, Jinan University, Guangzhou 510632, China
Interests: control and safety of multi-agent systems; intelligent control; dynamic neural networks

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Guest Editor
Department of Plant and Environmental Science, University of Copenhagen, Copenhagen, Denmark
Interests: artificial neural networks; multi-robots; machine learning; dynamic systems
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Guest Editor Assistant
Department of Building and Real Estate, The Hong Kong Polytechnic University (PolyU), Hong Kong
Interests: AI; machine learning; wireless sensor; complex networks; optimization and control; intelligent systems
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Special Issue Information

Dear Colleagues,

Intelligent control and computing manage control and computing problems by leveraging intelligent algorithms such as neural networks, fuzzy systems, and evolutionary computation. While many studies on intelligent control and computing have been published in recent decades, efforts dedicated to solving symmetry and asymmetry issues in intelligent control and computing problems and methods have seldom been reported. In control problems, such as the kinematic or dynamic control of robot manipulators, input constraints can be symmetric or asymmetric, and asymmetric input constraints are often considered a challenging issue. In this Special Issue, we aim to discuss the latest developments in addressing symmetry and asymmetry issues in intelligent control and computing problems and novel methods or algorithms for intelligent control and computing by leveraging symmetry and asymmetry.

Prof. Dr. Yinyan Zhang
Dr. Ameer Tamoor Khan
Guest Editors

Dr. Mohammed Aquil Mirza
Guest Editor Assistant

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Keywords

  • intelligent control
  • computing
  • symmetry
  • asymmetry
  • robotics

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Published Papers (1 paper)

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Research

19 pages, 1053 KiB  
Article
Symmetry-Aware Dynamic Scheduling Optimization in Hybrid Manufacturing Flexible Job Shops Using a Time Petri Nets Improved Genetic Algorithm
by Xuanye Lin, Zhenxiong Xu, Shujun Xie, Fan Yang, Juntao Wu and Deping Li
Symmetry 2025, 17(6), 907; https://doi.org/10.3390/sym17060907 - 8 Jun 2025
Abstract
Dynamic scheduling in hybrid flexible job shops (HFJSs) presents a critical challenge in modern manufacturing systems, particularly under dynamic and uncertain conditions. These systems often exhibit inherent structural and behavioral symmetry, such as uniform machine–job relationships and repeatable event response patterns. To leverage [...] Read more.
Dynamic scheduling in hybrid flexible job shops (HFJSs) presents a critical challenge in modern manufacturing systems, particularly under dynamic and uncertain conditions. These systems often exhibit inherent structural and behavioral symmetry, such as uniform machine–job relationships and repeatable event response patterns. To leverage this, we propose a time Petri nets (TPNs) model that integrates time and logic constraints, capturing symmetric processing and setup behaviors across machines as well as dynamic job and machine events. A transition select coding mechanism is introduced, where each transition node is assigned a normalized priority value in the range [0, 1], preserving scheduling consistency and symmetry during decision-making. Furthermore, we develop a symmetry-aware time Petri nets-based improved genetic algorithm (TPGA) to solve both static and dynamic scheduling problems in HFJSs. Experimental evaluations show that TPGA significantly outperforms classical dispatching rules such as Shortest Job First (SJF) and Highest Response Ratio Next (HRN), achieving makespan reductions of 23%, 10%, and 13% in process, discrete, and hybrid manufacturing scenarios, respectively. These results highlight the potential of exploiting symmetry in system modeling and optimization for enhanced scheduling performance. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Intelligent Control and Computing)
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