A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm
The Team Formation Problem (TFP) has recently gained popularity in Operation Research (OR) . The challenge of finding the lowest or maximum values from a massive pool of solutions is called optimization. Often, meta-heuristic algorithms are chosen to solve optimization issues because they are fast a...
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2022
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| Online Access: | http://umpir.ump.edu.my/id/eprint/35985/ http://umpir.ump.edu.my/id/eprint/35985/1/A%20Population%20Division%20Based%20Multi-Task%20Optimization%20Algorithm.pdf http://umpir.ump.edu.my/id/eprint/35985/7/A%20Population%20Division%20Based%20Multi-Task%20Optimization.pdf |
| _version_ | 1848824922623705088 |
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| author | Ahmmed, Mohammad Badal Kamal Z., Zamli |
| author_facet | Ahmmed, Mohammad Badal Kamal Z., Zamli |
| author_sort | Ahmmed, Mohammad Badal |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The Team Formation Problem (TFP) has recently gained popularity in Operation Research (OR) . The challenge of finding the lowest or maximum values from a massive pool of solutions is called optimization. Often, meta-heuristic algorithms are chosen to solve optimization issues because they are fast and use few resources. Recent literature research has focused on a new optimization issue termed multi-task optimization (MTO). This article updates our ongoing efforts to address the MTO issue. Specifically, our research examines the use of Tiki-Taka, a football-inspired meta-heuristic algorithm, to solve the MTO issue by adopting a partitioned population method. We use UMP Experts dataset as a case study to optimize team connection costs. Our study proved that TTA could solve MTO Team Formation Problem effectively. |
| first_indexed | 2025-11-15T03:20:44Z |
| format | Conference or Workshop Item |
| id | ump-35985 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:20:44Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-359852022-12-28T05:05:06Z http://umpir.ump.edu.my/id/eprint/35985/ A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm Ahmmed, Mohammad Badal Kamal Z., Zamli QA76 Computer software The Team Formation Problem (TFP) has recently gained popularity in Operation Research (OR) . The challenge of finding the lowest or maximum values from a massive pool of solutions is called optimization. Often, meta-heuristic algorithms are chosen to solve optimization issues because they are fast and use few resources. Recent literature research has focused on a new optimization issue termed multi-task optimization (MTO). This article updates our ongoing efforts to address the MTO issue. Specifically, our research examines the use of Tiki-Taka, a football-inspired meta-heuristic algorithm, to solve the MTO issue by adopting a partitioned population method. We use UMP Experts dataset as a case study to optimize team connection costs. Our study proved that TTA could solve MTO Team Formation Problem effectively. 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/35985/1/A%20Population%20Division%20Based%20Multi-Task%20Optimization%20Algorithm.pdf pdf en http://umpir.ump.edu.my/id/eprint/35985/7/A%20Population%20Division%20Based%20Multi-Task%20Optimization.pdf Ahmmed, Mohammad Badal and Kamal Z., Zamli (2022) A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm. In: The 6th National Conference for Postgraduate Research (NCON-PGR 2022) , 15 November 2022 , Virtual Conference, Universiti Malaysia Pahang, Malaysia. p. 53.. (Published) https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files |
| spellingShingle | QA76 Computer software Ahmmed, Mohammad Badal Kamal Z., Zamli A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm |
| title | A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm |
| title_full | A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm |
| title_fullStr | A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm |
| title_full_unstemmed | A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm |
| title_short | A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm |
| title_sort | population division based multi-task optimization algorithm for solving multiple-team formation problem based on tiki-taka optimization algorithm |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/35985/ http://umpir.ump.edu.my/id/eprint/35985/ http://umpir.ump.edu.my/id/eprint/35985/1/A%20Population%20Division%20Based%20Multi-Task%20Optimization%20Algorithm.pdf http://umpir.ump.edu.my/id/eprint/35985/7/A%20Population%20Division%20Based%20Multi-Task%20Optimization.pdf |