Hybrid Particle Swarm Optimization-Jaya Algorithm for Team Formation

Collaboration in a network is crucial for effective team formation. This paper addresses challenges in collaboration networks by identifying the skills required for effective team formation. The communication cost is low when agents with the same skills are connected. Our main objective is to minimize team communication costs by selecting agents with the required skills. However, finding an optimal team is a computationally hard problem. This study introduces a novel hybrid approach called I-PSO-Jaya (improved PSO-Jaya, which combines PSO (Particle Swarm Optimization) and the Jaya algorithm with the Modified Swap Operator to form efficient teams. A potential application scenario of the algorithm is to build a team of engineers for an IT project. The implementation results show that our approach gives an improvement of 73% in the Academia dataset and 92% in the ACM dataset compared to existing methods.

Authors

Institutions

Publication Details

Journal
Algorithms
Published
2024-08-26
DOI
https://doi.org/10.3390/a17090379
Citations
3
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
1.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hybrid Particle Swarm Optimization-Jaya Algorithm for Team Formation

Sandip Shingade, Rajdeep Niyogi, Mayuri Pichare
3 citations
Algorithms
Metaheuristic Optimization Algorithms Research
1.04
article

Hybrid Particle Swarm Optimization-Jaya Algorithm for Team Formation

Sandip Shingade, Rajdeep Niyogi, Mayuri Pichare
article en
3 citations

Abstract

Collaboration in a network is crucial for effective team formation. This paper addresses challenges in collaboration networks by identifying the skills required for effective team formation. The communication cost is low when agents with the same skills are connected. Our main objective is to minimize team communication costs by selecting agents with the required skills. However, finding an optimal team is a computationally hard problem. This study introduces a novel hybrid approach called I-PSO-Jaya (improved PSO-Jaya, which combines PSO (Particle Swarm Optimization) and the Jaya algorithm with the Modified Swap Operator to form efficient teams. A potential application scenario of the algorithm is to build a team of engineers for an IT project. The implementation results show that our approach gives an improvement of 73% in the Academia dataset and 92% in the ACM dataset compared to existing methods.

AlgorithmsVol. 17(9)
Indian Institute of Technology Roorkee (IN)
Openalex Percentile: Top 19%
Metaheuristic Optimization Algorithms Research
1.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.