{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:21:18Z","timestamp":1760145678107,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T00:00:00Z","timestamp":1724630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/a17090379","type":"journal-article","created":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T03:51:06Z","timestamp":1724730666000},"page":"379","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Hybrid Particle Swarm Optimization-Jaya Algorithm for Team Formation"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9625-6948","authenticated-orcid":false,"given":"Sandip","family":"Shingade","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1664-4882","authenticated-orcid":false,"given":"Rajdeep","family":"Niyogi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5692-5650","authenticated-orcid":false,"given":"Mayuri","family":"Pichare","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering and IT, Veermata Jijabai Technological Institute, Matunga, Mumbai 400019, India"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1007\/s10458-010-9136-3","article-title":"Towards efficient multiagent task allocation in the robocup rescue: A biologically-inspired approach","volume":"22","author":"Bazzan","year":"2011","journal-title":"Auton. 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