| _version_ | 1866901331926581248 |
|---|---|
| author | Pushkar Pattiwar Dhiraj Wadile Reva Pawar |
| author_facet | Pushkar Pattiwar Dhiraj Wadile Reva Pawar |
| contents | This research paper explores the transition from manual to automated resource allocation systems, leveraging Artificial Intelligence (AI) and Machine Learning (ML) tech- nologies. It addresses challenges such as dynamic allocation, optimization, and scalability across various sectors while outlining structured implementation approaches and potential applications in workforce management, pricing optimization, healthcare, and energy allocation. Advocating for continu- ous improvement through advanced technologies to enhance resource distribution effectiveness and fairness, the paper also discusses the implementation of an adaptable judge allocation module. Characterized by versatility and flexibility, this module is designed to accommodate diverse requirements and constraints, seamlessly integrating with any system and offering enhanced allocation capabilities tailored to specific needs. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18139307 |
| institution | Zenodo |
| language | |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | From Manual to Automated: Transforming Resource Allocation Pushkar Pattiwar Dhiraj Wadile Reva Pawar Automated Allocation This research paper explores the transition from manual to automated resource allocation systems, leveraging Artificial Intelligence (AI) and Machine Learning (ML) tech- nologies. It addresses challenges such as dynamic allocation, optimization, and scalability across various sectors while outlining structured implementation approaches and potential applications in workforce management, pricing optimization, healthcare, and energy allocation. Advocating for continu- ous improvement through advanced technologies to enhance resource distribution effectiveness and fairness, the paper also discusses the implementation of an adaptable judge allocation module. Characterized by versatility and flexibility, this module is designed to accommodate diverse requirements and constraints, seamlessly integrating with any system and offering enhanced allocation capabilities tailored to specific needs. |
| title | From Manual to Automated: Transforming Resource Allocation |
| topic | Automated Allocation |
| url | https://doi.org/10.5281/zenodo.18139307 |