Jaya R Package -- A Parameter-Free Solution for Advanced Single and Multi-Objective Optimization
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866915033469943808 |
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| author | Bokde, Neeraj Dhanraj |
| author_facet | Bokde, Neeraj Dhanraj |
| contents | The Jaya R package offers a robust and versatile implementation of the parameter-free Jaya optimization algorithm, suitable for solving both single-objective and multi-objective optimization problems. By integrating advanced features such as constraint handling, adaptive population management, Pareto front tracking for multi-objective trade-offs, and parallel processing for computational efficiency, the package caters to a wide range of optimization challenges. Its intuitive design and flexibility allow users to solve complex, real-world problems across various domains. To demonstrate its practical utility, a case study on energy modeling explores the optimization of renewable energy shares, showcasing the package's ability to minimize carbon emissions and costs while enhancing system reliability. The Jaya R package is an invaluable tool for researchers and practitioners seeking efficient and adaptive optimization solutions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_16509 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Jaya R Package -- A Parameter-Free Solution for Advanced Single and Multi-Objective Optimization Bokde, Neeraj Dhanraj Mathematical Software Machine Learning The Jaya R package offers a robust and versatile implementation of the parameter-free Jaya optimization algorithm, suitable for solving both single-objective and multi-objective optimization problems. By integrating advanced features such as constraint handling, adaptive population management, Pareto front tracking for multi-objective trade-offs, and parallel processing for computational efficiency, the package caters to a wide range of optimization challenges. Its intuitive design and flexibility allow users to solve complex, real-world problems across various domains. To demonstrate its practical utility, a case study on energy modeling explores the optimization of renewable energy shares, showcasing the package's ability to minimize carbon emissions and costs while enhancing system reliability. The Jaya R package is an invaluable tool for researchers and practitioners seeking efficient and adaptive optimization solutions. |
| title | Jaya R Package -- A Parameter-Free Solution for Advanced Single and Multi-Objective Optimization |
| topic | Mathematical Software Machine Learning |
| url | https://arxiv.org/abs/2411.16509 |