A Solution for the Team Selection Problem Using ACO

被引：0

作者：

Lugo, Lazaro ^{[1
]}

Bello, Marilyn ^{[1
,2
]}

Nowe, Ann ^{[3
]}

Bello, Rafael ^{[1
]}

机构：

[1] Univ Cent Marta Abreu Las Villas, Dept Comp Sci, Santa Clara, Cuba

[2] Hasselt Univ, Fac Business Econ, Hasselt, Belgium

[3] Vrije Univ Brussel, Artificial Intelligence Lab, Brussels, Belgium

来源：

SWARM INTELLIGENCE (ANTS 2018) | 2018年 / 11172卷

关键词：

ANT COLONY; SYSTEM; OPTIMIZATION;

D O I：

10.1007/978-3-030-00533-7_26

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The team selection problem is usually solved by ranking candidates based on the preferences of decision-makers and allowing the decision-makers to take turns selecting candidates. While this solution method is simple and might seem fair it usually results in an unfair allocation of candidates to the different teams, i.e. the quality of the teams might be quite different according to the rankings articulated by the decision-makers. In this paper, we propose a new method based on Ant Colony Optimization (ACO), where the selection process is performed in a new context, with more than two decision-makers selecting from a common set of candidates. Furthermore, a plugin implementing this method for the KNIME platform was developed.

引用

页码：325 / 332

页数：8

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