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Symmetry
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Symmetry/Asymmetry in Operations Research
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Symmetry/Asymmetry in Operations Research

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

Deadline for manuscript submissions: 31 July 2025 | Viewed by 7989

Special Issue Editors

Dr. Yunfei Fang

E-Mail Website
Guest Editor
School of Economics and Management, Fuzhou University, Fuzhou, China
Interests: operation research management; intelligent optimization; logistics and transportation; transportation planning
Prof. Dr. Peng Wu

E-Mail Website
Guest Editor
School of Economics and Management, Fuzhou University, Fuzhou, China
Interests: the optimization of complex transportation and production systems based on operations research, evacuation management

Special Issue Information

Dear Colleagues,

Operations research (OR) is an analytical method of problem-solving and decision-making that enables us to achieve the best performance under the given circumstances. It is an interdisciplinary science involving statistical analysis, optimization theory, industrial and systems engineering, management science, Artificial Intelligence, and computer science, etc. Due to its power to handle sophisticated and practical problems, it is being widely applied to various areas, such as supply chains, logistics, production and scheduling, intelligent manufacturing, smart health, transportation planning, operation management, and engineering design. Though symmetry/asymmetry phenomena are observed in most of the aforementioned areas, as with logistics and supply chains, symmetry/asymmetry in OR has not been thoroughly investigated. This Special Issue “Symmetry/Asymmetry in Operations Research” focuses on the methodologies and applications of OR involving symmetry/asymmetry phenomena. It aims to attract high-quality studies of original OR contributions and to promote theoretical developments and real-world implementations in relevant fields. Research areas may include (but are not limited to) the following:

  • Supply chains management;
  • Production and scheduling;
  • Routing optimization in logistics;
  • Intelligent transportation system;
  • Intelligent manufacturing;
  • Smart health;
  • Operation management;
  • Optimization algorithm.

We look forward to receiving your contributions.

Dr. Yunfei Fang
Prof. Dr. Peng Wu
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

  • supply chains management
  • production scheduling
  • routing optimization
  • transportation planning
  • intelligent manufacturing
  • operation management
  • optimization algorithm
  • mixed-integer programming

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Published Papers (7 papers)

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Research

14 pages, 4923 KiB  
Article
Probabilistic Multi-Robot Task Scheduling for the Antarctic Environments with Crevasses
by Seokjin Kang and Heoncheol Lee
Symmetry 2024, 16(9), 1229; https://doi.org/10.3390/sym16091229 - 19 Sep 2024
Viewed by 557
Abstract
This paper deals with the problem of multi-robot task scheduling in the Antarctic environments with crevasses. Because the crevasses may cause hazardous situations when robots are operated in the Antarctic environments, robot navigation should be planned to safely avoid the positions of crevasses. [...] Read more.
This paper deals with the problem of multi-robot task scheduling in the Antarctic environments with crevasses. Because the crevasses may cause hazardous situations when robots are operated in the Antarctic environments, robot navigation should be planned to safely avoid the positions of crevasses. However, the positions of the crevasses may be inaccurately measured due to the lack of sensor performance, the asymmetry of sensor data, and the possibility of crevasses drifting irregularly as time passes. To overcome these uncertain and asymmetric problems, this paper proposes a probabilistic multi-robot task scheduling method based on the Nearest Neighbors Test (NNT) algorithm and the probabilistic modeling of the positions of crevasses. The proposed method was tested with a Google map of the Antarctic environments and showed a better performance than the Ant Colony Optimization (ACO) algorithm and the Genetic Algorithm (GA) in the context of total cost and computational time. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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15 pages, 861 KiB  
Article
A Unified Hardware Design for Multiplication, Division, and Square Roots Using Binary Logarithms
by Dat Ngo, Siyeon Han and Bongsoon Kang
Symmetry 2024, 16(9), 1138; https://doi.org/10.3390/sym16091138 - 2 Sep 2024
Viewed by 915
Abstract
Multiplication, division, and square root operations introduce significant challenges in digital signal processing (DSP) systems, traditionally requiring multiple operations that increase execution time and hardware complexity. This study presents a novel approach that leverages binary logarithms to perform these operations using only addition, [...] Read more.
Multiplication, division, and square root operations introduce significant challenges in digital signal processing (DSP) systems, traditionally requiring multiple operations that increase execution time and hardware complexity. This study presents a novel approach that leverages binary logarithms to perform these operations using only addition, subtraction, and shifts, enabling a unified hardware implementation—a marked departure from conventional methods that handle these operations separately. The proposed design, involving logarithm and antilogarithm calculations, exhibits an algebraically symmetrical pattern that further optimizes the processing flow. Additionally, this study introduces innovative log-domain correction terms specifically designed to minimize computation errors—a critical improvement over existing methods that often struggle with precision. Compared to standard hardware implementations, the proposed design significantly reduces hardware resource utilization and power consumption while maintaining high operational frequency. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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23 pages, 4721 KiB  
Article
The Influence of the Assembly Line Configuration and Reliability Parameter Symmetry on the Key Performance Indicators
by Adrian Kampa and Iwona Paprocka
Symmetry 2024, 16(9), 1128; https://doi.org/10.3390/sym16091128 - 31 Aug 2024
Viewed by 996
Abstract
In the context of the demand for mass customization of products, a trade-off between highly efficient automated systems and flexible manual operators is sought. The linear arrangement of workstations made it possible to divide the process into many simple operations, which increases production [...] Read more.
In the context of the demand for mass customization of products, a trade-off between highly efficient automated systems and flexible manual operators is sought. The linear arrangement of workstations made it possible to divide the process into many simple operations, which increases production efficiency, but also results in an increase in the number of workstations and a significant extension of the line. A human operator is usually treated as a quasi-mechanical object, and a human error is considered, similarly, as a failure of a technical component. However, human behavior is more complex and difficult to predict. A mathematical model of a new production organization is presented, including dividing the traditional production line into shorter sections or replacing the serial assembly line with a U-line with cells. Moreover, the reliability of operator and technical means are distinguished. Work-in-progress inventories are located between line sections to improve system stability. The stability of the assembly line is examined based on the system configuration and probabilistic estimates of human failure. The influence of the symmetry of reliability parameters of people on key performance indicators (KPI (headcount), KPI (surface) and KPI (Overall Equipment Effectiveness) is examined. KPI (solution robustness) and KPI (quality robustness) are also presented in order to evaluate the impact of a disruption on the assembly line performance. New rules for assigning tasks to stations are proposed, taking into account the risk of disruptions in the execution of tasks. For comparison of assembly problems, heuristic methods with newly developed criteria are used. The results show the impact of symmetry/asymmetry on assembly line performance and an asymmetric distribution of manual assembly times that is significantly skewed to the right due to human errors. On the assembly line, the effects of these errors are cumulative and lead to longer assembly times and lower KPIs. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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34 pages, 4306 KiB  
Article
Post-Earthquake Emergency Logistics Location-Routing Optimization Considering Vehicle Three-Dimensional Loading Constraints
by Xujin Pu and Xu Zhao
Symmetry 2024, 16(8), 1080; https://doi.org/10.3390/sym16081080 - 20 Aug 2024
Viewed by 976
Abstract
An efficient humanitarian emergency logistics network is vital in responding to earthquake disasters. However, the asymmetric information inherent in the location and distribution stages can complicate the humanitarian emergency logistics network designing process, resulting in an asymmetric optimization problem. This paper addresses a [...] Read more.
An efficient humanitarian emergency logistics network is vital in responding to earthquake disasters. However, the asymmetric information inherent in the location and distribution stages can complicate the humanitarian emergency logistics network designing process, resulting in an asymmetric optimization problem. This paper addresses a multi-objective humanitarian emergency logistics network design problem during the earthquake response phase. The objective is to reduce societal expenses (e.g., logistical and deprivation costs) and mitigate risk to the logistics network by identifying ideal sites for distribution hubs, optimal emergency material distribution strategies, and precise material loading plans. The proposed model takes into account various constraint types, such as 3D loading limitations for relief materials, interruptions in distribution hubs, distribution centers’ capacity, transport vehicles’ capacity, and specific time windows for demand points. First, a multi-objective mixed-integer programming model is established to solve the problem. Uncertainty is modeled using a scenario-based probability approach. Second, a multi-objective genetic algorithm based on adaptive large neighborhood search (MOGA-ALNS) is designed to further optimize the solutions obtained from the evolutionary process using an adaptive large neighborhood search algorithm. Furthermore, the MOGA-ALNS integrates a simulated annealing process in the neighborhood search stage to inhibit the algorithm from reaching local optimums. Ultimately, the MOGA-ALNS is compared to three additional multi-objective optimization algorithms. The comprehensive analysis and discussion conducted unequivocally validate the competitiveness and efficacy of the proposed approach. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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20 pages, 3632 KiB  
Article
A Systematic Formulation into Neutrosophic Z Methodologies for Symmetrical and Asymmetrical Transportation Problem Challenges
by Muhammad Kamran, Manal Elzain Mohamed Abdalla, Muhammad Nadeem, Anns Uzair, Muhammad Farman, Lakhdar Ragoub and Ismail Naci Cangul
Symmetry 2024, 16(5), 615; https://doi.org/10.3390/sym16050615 - 15 May 2024
Cited by 1 | Viewed by 925
Abstract
This study formulates a multi-objective, multi-item solid transportation issue with parameters that are neutrosophic Z-number fuzzy variables such as transportation costs, supplies, and demands. This work covers two scenarios where uncertainty in the problem can arise: the fuzzy solid transportation problem and the [...] Read more.
This study formulates a multi-objective, multi-item solid transportation issue with parameters that are neutrosophic Z-number fuzzy variables such as transportation costs, supplies, and demands. This work covers two scenarios where uncertainty in the problem can arise: the fuzzy solid transportation problem and the interval solid transportation problem. The first scenario arises when we represent data problems as intervals instead of exact values, while the second scenario arises when the information is not entirely clear. We address both models when the uncertainty alone impacts the constraint set. In order to find a solution for the interval case, we generate an additional problem. Since this auxiliary problem is typical of solid transportation, we can resolve it using the effective techniques currently in use. In the fuzzy scenario, a parametric method is used to discover a fuzzy solution to the earlier issue. Parametric analysis identifies that the best parameterized approaches to complementary problems are characterized by the application of parametric analysis. We present a suggested algorithm for determining the stability set. Finally, we provide a numerical example and sensitivity analysis for the transportation problem, which is both symmetrical and asymmetrical. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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16 pages, 461 KiB  
Article
An Exploration of Multitasking Scheduling Considering Interruptible Job Assignments, Machine Aging Effects, the Influence of Deteriorating Maintenance, and Symmetry
by Li Zeng
Symmetry 2024, 16(3), 380; https://doi.org/10.3390/sym16030380 - 21 Mar 2024
Viewed by 1162
Abstract
The unique topic of allocating and scheduling tasks on a single machine in a multitasking environment is the main emphasis of this research, which also takes into account the effects of worsening maintenance and job-dependent aging effects. In this scenario, the performance and [...] Read more.
The unique topic of allocating and scheduling tasks on a single machine in a multitasking environment is the main emphasis of this research, which also takes into account the effects of worsening maintenance and job-dependent aging effects. In this scenario, the performance and efficiency of the machine in handling different tasks should be symmetric, without significant bias due to the nature or size of the tasks. In a multitasking environment, waiting for jobs can disrupt the processing of the primary job being currently handled. As a result, the actual time required to complete a task becomes erratic and contingent upon the duration of the disruption. In addition to figuring out the best time for maintenance, where to put the due-window, and how big it should be in a multitasking environment, the primary objective is to minimize the costs associated with meeting due-window regulations. To tackle this problem, we propose two optimal algorithms. Additionally, we conduct numerical experiments to compare our approach with the classic due date assignment problem. Interestingly, we observe that in most cases, the average and minimum percentage costs tend to increase as the quantity of jobs increases. However, it is noteworthy that, when the number of jobs is relatively small, specifically when it does not exceed 20, there are instances where these costs decrease with an increase in the number of jobs. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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37 pages, 6503 KiB  
Article
A Novel Hybrid MSA-CSA Algorithm for Cloud Computing Task Scheduling Problems
by Shtwai Alsubai, Harish Garg and Abdullah Alqahtani
Symmetry 2023, 15(10), 1931; https://doi.org/10.3390/sym15101931 - 18 Oct 2023
Cited by 4 | Viewed by 1654
Abstract
Recently, the dynamic distribution of resources and task scheduling has played a critical role in cloud computing to achieve maximum storage and performance. The allocation of computational tasks in the cloud is a complicated process that can be affected by some factors, such [...] Read more.
Recently, the dynamic distribution of resources and task scheduling has played a critical role in cloud computing to achieve maximum storage and performance. The allocation of computational tasks in the cloud is a complicated process that can be affected by some factors, such as available network bandwidth, makespan, and cost considerations. However, these allocations are always non-symmetric. Therefore, it is crucial to optimize available bandwidth for efficient cloud computing task scheduling. In this research, a novel swarm-based task scheduling with a security approach is proposed to optimize the distribution of tasks using available resources and encode cloud information during task scheduling. It can combine the Moth Swarm Algorithm (MSA) with the Chameleon Swarm Algorithm (CSA) for the task scheduling process and utilizes the Polymorphic Advanced Encryption Standard (P-AES) for information security of cloud scheduled tasks. The approach offers a new perspective for utilizing swarm intelligence algorithms to optimize cloud task scheduling. The integration of MSA and CSA with P-AES enables the approach to provide efficient and secure task scheduling by exploiting the strengths of used algorithms. The study evaluates the performance of the proposed approach in terms of the degree of imbalance, makespan, resource utilization, cost, average waiting time, response time, throughput, latency, execution time, speed, and bandwidth utilization. The simulation is carried out using a wide range of tasks from 1000 to 5000. The results show that the approach provides an innovative solution to the challenges of task scheduling in cloud environments and improves the performance of cloud services in terms of effectiveness and security measures. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)
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