Research Area:  Metaheuristic Computing

Abstract:

Team composition is one of the most important and challenging directions in the recommendation problem. Compared with a single person, the advantage of a team is mainly reflected in the synergy of team members complementary collaboration. To build a high-efficiency team, how to choose the team members has become a tricky problem. However, there is a lack of quantitative algorithms and validation methods for team member selection. In this paper, we put forward three indicators to measure a teams ability and formulate the selection of football team members as a multi-objective optimization problem. Subsequently, an evolutionary player selection algorithm based on the genetic algorithm is proposed to solve the team composition problem. We verify the effectiveness of the team member recommendation algorithm via data analysis, football game simulation under different budget constraints and provide comparisons with existing methods.

Keywords:  
football game
team composition
recommendation problem
complementary collaboration
quantitative algorithm
validation method
multi-objective optimization problem

Author(s) Name:  Haoyu Zhao, Haihui Chen, Shenbao Yu, Bilian Chen

Publisher name:  IEEE

DOI:  10.1109/ACCESS.2021.3091185

Volume Information:  Volume: 9

Paper Link:   https://ieeexplore.ieee.org/abstract/document/9461759