Title: A collective intelligence based project team formation using bio-inspired techniques

Authors: Ankita Verma; Vaishnavi Agarwal; Shubhangi; Sakeena Rizvi; Savita Singh

Addresses: Jaypee Institute of Information Technology, A-10, Sector-62, Noida-201 309, Uttar Pradesh, India ' Jaypee Institute of Information Technology, A-10, Sector-62, Noida-201 309, Uttar Pradesh, India ' Jaypee Institute of Information Technology, A-10, Sector-62, Noida-201 309, Uttar Pradesh, India ' Jaypee Institute of Information Technology, A-10, Sector-62, Noida-201 309, Uttar Pradesh, India ' Gurukul Kangri Vishwavidyalaya (Deemed to be University), Jagjeetpur, Haridwar, 249404, Uttarakhand, India

Abstract: The outcome of a project is greatly influenced by technical variables along with human and social elements of the development process. The knowledge possessed by team members and their ability to collaborate effectively are essential in managing these complexities. Team formation involves assembling specialists with diverse skills to perform a task efficiently. This paper addresses team formation for generalised tasks by formulating a set of experts from an expertise network who can collaborate effectively. It utilises collective intelligence to build teams, maximising potential based on individual skill levels. The proposed model captures team dynamics by considering trust, which is vital for effective interactions. Team formation is formulated as an optimisation problem with two objectives: 1) maximising knowledge; 2) maximising collaboration. To achieve this, nature-inspired approaches such as NSGA-II and ant colony optimisation (ACO) are employed. Results demonstrate the method's effectiveness from both computational and pedagogical perspectives.

Keywords: team formation; collective intelligence; bio-inspired computing; genetic algorithm; project development.

DOI: 10.1504/IJBIDM.2026.151274

International Journal of Business Intelligence and Data Mining, 2026 Vol.28 No.1, pp.60 - 79

Received: 06 Dec 2024
Accepted: 16 Sep 2025
Published online: 20 Jan 2026 *

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