A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm

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..

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DOI/Official URL: https://ncon-pgr.ump.edu.my/index.php/en/?option=c...

Abstract

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.

Item Type:	Conference or Workshop Item (Lecture)
Uncontrolled Keywords:	Optimization; Meta-heuristic Algorithm; Team Formation Problem(TFP); Multi-Task Optimization(MTO)
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Faculty/Division:	Institute of Postgraduate Studies Faculty of Computing
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	28 Dec 2022 05:05
Last Modified:	28 Dec 2022 05:05
URI:	http://umpir.ump.edu.my/id/eprint/35985
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