An Approach for Team Formation Using Modified Grey Wolf Optimizer

被引：1

作者：

Shingade, Sandip T. ^{[1
]}

Niyogi, Rajdeep ^{[1
]}

机构：

[1] Indian Inst Technol Roorkee, Roorkee 247667, Uttar Pradesh, India

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2023, PT I | 2023年 / 13956卷

关键词：

Team formation; GWO; JAYA; IGWO; ALGORITHM;

D O I：

10.1007/978-3-031-36805-9_29

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 formation problem is to find a subset of agents, referred to as a team, from a given set of agents such that the team satisfies some desirable property. The computational complexity of this problem is known to be NP-hard. In this paper, we suggest a modified grey wolf optimization approach to find a team with minimum communication cost. The proposed algorithm is evaluated with two real-world data sets, namely the ACM data set and the Academia Stack exchange data set. The experimental results show that the algorithm outperforms some existing approaches with respect to some parameters.

引用

页码：440 / 452

页数：13

共 14 条

[11] A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristics [J].

Moreno, Julian ;

Ovalle, Demetrio A. ;

Vicari, Rosa M. .

COMPUTERS & EDUCATION, 2012, 58 (01) :560-569

[12] A self-adaptive multi-population based Jaya algorithm for engineering optimization [J].

Rao, R. Venkata ;

Saroj, Ankit .

SWARM AND EVOLUTIONARY COMPUTATION, 2017, 37 :1-26

[13] A novel state space reduction algorithm for team formation in social networks [J].

Rehman, Muhammad Zubair ;

Zamli, Kamal Z. ;

Almutairi, Mubarak ;

Chiroma, Haruna ;

Aamir, Muhammad ;

Kader, Md Abdul ;

Nawi, Nazri Mohd .

PLOS ONE, 2021, 16 (12)

[14]

Venkata Rao R., 2016, Int. J. Ind. Eng. Comput, V7, P19, DOI [10.5267/j.ijiec.2015.8.004, DOI 10.5267/J.IJIEC.2015.8.004]

← 1 2 →