Comparative study of five metaheuristic algorithms for team formation problem
This paper presents a comparative study of five metaheuristic algorithms, namely, salp swarm algorithm (SSA), owl search algorithm (OSA), sooty tern optimization algorithm (STOA), squirrel search algorithm (SqSA), and crow search algorithm (CSA) adopted in the Covid19 team formation (CTF) problem. T...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Springer
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/32780/1/18.%20Comparative%20study%20of%20five%20metaheuristic%20algorithms%20for%20team%20formation%20problem.pdf http://umpir.ump.edu.my/id/eprint/32780/2/18.1%20Comparative%20study%20of%20five%20metaheuristic%20algorithms%20for%20team%20formation%20problem.pdf |
| Summary: | This paper presents a comparative study of five metaheuristic algorithms, namely, salp swarm algorithm (SSA), owl search algorithm (OSA), sooty tern optimization algorithm (STOA), squirrel search algorithm (SqSA), and crow search algorithm (CSA) adopted in the Covid19 team formation (CTF) problem. The performance comparison of these algorithms is conducted by executing each algorithm twenty times to ensure the statistical significance. The study considers the minimum number of experts and the minimum team formation cost in defining the objective function. The CSA was found to be the more effective metaheuristic algorithm for the Covid19 team formation problem from the optimal results in terms of overall solution quality and runtime efficiency. |
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