{"paper":{"title":"Indian Wedding System Optimization (IWSO): A Novel Socially Inspired Metaheuristic with Operational Design and Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"IWSO models Indian wedding matchmaking as a guided search that lets elite solutions steer weaker ones while eliminating poor performers to maintain diversity.","cross_cats":["cs.LG"],"primary_cat":"cs.NE","authors_text":"Ashutosh Kumar Singh, Deepika Saxena, Jatinder Kumar, Jitendra Kumar, Kishu Gupta, Niharika Singh, Sakshi Patni, Vinaytosh Mishra","submitted_at":"2026-05-05T08:57:52Z","abstract_excerpt":"This paper presents a novel population-based metaheuristic, Indian Wedding System Optimization (IWSO), inspired by the socio-cultural dynamics of traditional Indian weddings. IWSO models the matchmaking process driven by collaboration among families, candidates, and matchmakers as a guided, selective search framework for solving complex optimization problems. The algorithm introduces two key innovations: (i) a matchmaker-guided influence strategy, where elite solutions direct the evolution of weaker candidates, enhancing convergence without external parameters; and (ii) an adaptive elimination"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Extensive experiments on benchmark high-dimensional and multimodal test functions demonstrate superior performance of IWSO in terms of convergence speed, solution quality, and robustness.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the matchmaker-guided influence strategy and adaptive elimination mechanism translate the social analogy into algorithmic improvements that hold without hidden parameter tuning or benchmark-specific biases.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"IWSO is a new metaheuristic using matchmaker-guided elite influence and adaptive elimination-reinitialization to achieve faster convergence and higher solution quality than GA, PSO, DE, and CS on high-dimensional benchmark functions.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"IWSO models Indian wedding matchmaking as a guided search that lets elite solutions steer weaker ones while eliminating poor performers to maintain diversity.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"e550ccb584a6f9c9ec0dc115df24729b9fea14156d4f7cfb20e7c693c9e7cc79"},"source":{"id":"2605.13871","kind":"arxiv","version":1},"verdict":{"id":"ae888a8d-7c71-4301-a8b4-29644845ec19","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T07:09:01.881071Z","strongest_claim":"Extensive experiments on benchmark high-dimensional and multimodal test functions demonstrate superior performance of IWSO in terms of convergence speed, solution quality, and robustness.","one_line_summary":"IWSO is a new metaheuristic using matchmaker-guided elite influence and adaptive elimination-reinitialization to achieve faster convergence and higher solution quality than GA, PSO, DE, and CS on high-dimensional benchmark functions.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the matchmaker-guided influence strategy and adaptive elimination mechanism translate the social analogy into algorithmic improvements that hold without hidden parameter tuning or benchmark-specific biases.","pith_extraction_headline":"IWSO models Indian wedding matchmaking as a guided search that lets elite solutions steer weaker ones while eliminating poor performers to maintain diversity."},"references":{"count":28,"sample":[{"doi":"","year":2013,"title":"X.-S. Yang, Z. Cui, R. Xiao, A. H. Gandomi, and M. Karamanoglu, Swarm intelligence and bio-inspired computation: theory and applica- tions. 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