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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: 30 November 2024 | Viewed by 2067

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

Published Papers (2 papers)

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Research

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 624
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 1 | Viewed by 1074
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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