Asymmetric and Symmetric Study on Algorithms Optimization
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 1952
Special Issue Editors
Interests: operational research; multicriteria; ELECTRE I, III, IV; PROMETHEE; latent dirichlet allocation; text mining; topic model; human resources; police; police education; public security
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Special Issue Information
Dear Colleagues,
Asymmetric Study:
In asymmetric algorithm optimization, the focus is on leveraging the unique strengths or characteristics of the different components or entities involved. This approach aims to maximize optimization by exploiting specific advantages of individual elements rather than trying to achieve balance across all components. Asymmetric study involves identifying and utilizing the specific capabilities or resources of each entity to enhance overall performance. This approach is suitable for problems where each entity has different characteristics or capabilities that can be harnessed for optimized solutions.
Symmetric Study:
Symmetric algorithm optimization focuses on achieving balanced or equally efficient solutions across multiple components or entities. The aim is to distribute resources, workloads, or computational tasks evenly to ensure fairness, equal processing time, and optimal utilization of resources. Techniques such as load balancing, parallel computing, and task scheduling are often used in symmetric study to achieve optimal performance across all entities involved. This approach is appropriate when the components or entities are homogeneous and do not possess distinct advantages or differences in capabilities.
In both asymmetric and symmetric algorithm optimization, the choice depends on the specific problem, the characteristics of the entities involved, and the desired outcome. By understanding these approaches, researchers and practitioners can select the most suitable strategy to achieve efficient and optimized algorithms.
Prof. Dr. Marcio Basilio
Dr. Valdecy Pereira
Guest Editors
Manuscript Submission Information
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Keywords
- symmetric algorithms
- balanced optimization
- equally efficient solutions
- resource distribution
- fairness
- parallel computing
- load balancing
- task scheduling
- homogeneous components
- optimal performance
