Improved employee bee algorithm for team formation

Sandip Shingade

doi:10.1007/s12530-025-09688-8

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Improved employee bee algorithm for team formation

2025-04-29

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Sandip Shingade *

Rajdeep Niyogi

Sushila Shelke

DOI：10.1007/s12530-025-09688-8

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Abstract

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Finding an appropriate subset of agents (a team) from a larger pool of agents (the source set) so that the team exhibits a desired quality is the essence of the team formation problem. This problem is recognized to have high computational complexity, classified as NP-hard. In order to reduce the state space, this research paper incorporates techniques including vertical and horizontal reductions, which convert data to binary representation. To simplify the data representation for analysis, these methods use vertical and horizontal reductions to convert data to binary format, generating a subgraph. With this, the Honeybee Optimization algorithm's Employee Bee phase (EBP) swap operation characteristic is used to efficiently optimize team communication costs by making it easier to determine a team with a minimum communication costs (MCC). The proposed approach is assessed using two well-known real-world data sets, the ACM data set and the DBLP data set, demonstrating an improvement of 79% in the ACM dataset and 68% in the DBLP dataset compared to existing literature approaches like Improved Jaya Modified Swap Operation, Improved Grey Wolf Optimization, and State Space Reduction Techniques for Team Formation. This highlights the significant positive impact of state space reduction techniques combined with the IEB on team performance, particularly enhancing communication efficiency and overall team effectiveness, as measured by MCC metrics.

Keywords:

Team Formation

Improved Jaya Modified Swap Operation

Swap Operation

State Space Reduction techniques