Advances in Machine Learning and Mathematical Modeling for Optimization Problems
Machine learning and deep learning have made tremendous progress over the last decade and have become the de facto standard across a wide range of image, video, text, and sound processing domains, from object recognition to image generation. Recently, deep learning and deep reinforcement learning ha...
Sábháilte in:
| Formáid: | Online |
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| Teanga: | Béarla |
| Foilsithe / Cruthaithe: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Ábhair: | |
| Rochtain ar líne: | ONIX_20230911_9783036577401_89 |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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| _version_ | 1869528726460432384 |
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| collection | Directory of Open Access Books |
| description | Machine learning and deep learning have made tremendous progress over the last decade and have become the de facto standard across a wide range of image, video, text, and sound processing domains, from object recognition to image generation. Recently, deep learning and deep reinforcement learning have begun to develop end-to-end training to solve more complex operation research and combinatorial optimization problems, such as covering problems, vehicle routing problems, traveling salesman problems, scheduling problems, and other complex problems requiring general simulations. These methods also sometimes include classic search and optimization algorithms for machine learning, such as Monte Carlo Tree Search in AlphaGO. The present reprint contains all of the articles accepted and published in the Special Issue of Mathematics entitled "Advances in Machine Learning and Mathematical Modeling for Optimization Problems”. The articles presented in this Special Issue provide insights into related fields, including models, performance evaluation and improvements, and application developments. We hope that readers will benefit from the insights of these papers and contribute to these rapidly growing areas. We also hope that this Special Issue will shed light on major developments in the area of machine learning and mathematical modeling for optimization problems and that it will attract the attention of the scientific community to pursue further investigations, leading to the rapid implementation of these techniques. |
| format | Online |
| id | doab-20.500.12854ir-113956 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1139562024-03-28T03:32:28Z Advances in Machine Learning and Mathematical Modeling for Optimization Problems Rivest, Francois Chehri, Abdellah machine learning deep reinforcement learning evolutionary computation artificial neural networks (ANNs) end-to-end learning feature selection statistical learning convex minimization problems optimization problems decision theory traveling salesman problem resource allocation vehicle routing problem pickup and delivery thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science Machine learning and deep learning have made tremendous progress over the last decade and have become the de facto standard across a wide range of image, video, text, and sound processing domains, from object recognition to image generation. Recently, deep learning and deep reinforcement learning have begun to develop end-to-end training to solve more complex operation research and combinatorial optimization problems, such as covering problems, vehicle routing problems, traveling salesman problems, scheduling problems, and other complex problems requiring general simulations. These methods also sometimes include classic search and optimization algorithms for machine learning, such as Monte Carlo Tree Search in AlphaGO. The present reprint contains all of the articles accepted and published in the Special Issue of Mathematics entitled "Advances in Machine Learning and Mathematical Modeling for Optimization Problems”. The articles presented in this Special Issue provide insights into related fields, including models, performance evaluation and improvements, and application developments. We hope that readers will benefit from the insights of these papers and contribute to these rapidly growing areas. We also hope that this Special Issue will shed light on major developments in the area of machine learning and mathematical modeling for optimization problems and that it will attract the attention of the scientific community to pursue further investigations, leading to the rapid implementation of these techniques. 2023-09-11T12:10:40Z 2023-09-11T12:10:40Z 2023 book ONIX_20230911_9783036577401_89 9783036577401 9783036577418 https://directory.doabooks.org/handle/20.500.12854/113956 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/7800 https://mdpi.com/books/pdfview/book/7800 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-7741-8 10.3390/books978-3-0365-7741-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036577401 9783036577418 280 open access |
| spellingShingle | machine learning deep reinforcement learning evolutionary computation artificial neural networks (ANNs) end-to-end learning feature selection statistical learning convex minimization problems optimization problems decision theory traveling salesman problem resource allocation vehicle routing problem pickup and delivery thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science Advances in Machine Learning and Mathematical Modeling for Optimization Problems |
| title | Advances in Machine Learning and Mathematical Modeling for Optimization Problems |
| title_full | Advances in Machine Learning and Mathematical Modeling for Optimization Problems |
| title_fullStr | Advances in Machine Learning and Mathematical Modeling for Optimization Problems |
| title_full_unstemmed | Advances in Machine Learning and Mathematical Modeling for Optimization Problems |
| title_short | Advances in Machine Learning and Mathematical Modeling for Optimization Problems |
| title_sort | advances in machine learning and mathematical modeling for optimization problems |
| topic | machine learning deep reinforcement learning evolutionary computation artificial neural networks (ANNs) end-to-end learning feature selection statistical learning convex minimization problems optimization problems decision theory traveling salesman problem resource allocation vehicle routing problem pickup and delivery thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science |
| topic_facet | machine learning deep reinforcement learning evolutionary computation artificial neural networks (ANNs) end-to-end learning feature selection statistical learning convex minimization problems optimization problems decision theory traveling salesman problem resource allocation vehicle routing problem pickup and delivery thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science |
| url | ONIX_20230911_9783036577401_89 |