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...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2022
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| Subjects: | |
| 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 |
| Summary: | 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. |
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