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pith:2026:HNXHZH2PXFNUBHKI2KWKEYA33K
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Indian Wedding System Optimization (IWSO): A Novel Socially Inspired Metaheuristic with Operational Design and Analysis

Ashutosh Kumar Singh, Deepika Saxena, Jatinder Kumar, Jitendra Kumar, Kishu Gupta, Niharika Singh, Sakshi Patni, Vinaytosh Mishra

IWSO models Indian wedding matchmaking as a guided search that lets elite solutions steer weaker ones while eliminating poor performers to maintain diversity.

arxiv:2605.13871 v1 · 2026-05-05 · cs.NE · cs.LG

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Claims

C1strongest 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.

C2weakest 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.

C3one 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.

References

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[1] X.-S. Yang, Z. Cui, R. Xiao, A. H. Gandomi, and M. Karamanoglu, Swarm intelligence and bio-inspired computation: theory and applica- tions. Newnes, 2013 2013
[2] A surrogate-assisted memetic algorithm for permutation-based combinatorial optimization problems, 2025
[3] Nature-inspired metaheuristic algorithms. luniver press, 2010, 2010
[4] Evolutionary transfer optimization-a new frontier in evolutionary computation research, 2021
[5] Ant colony optimization algorithms for dynamic optimization: A case study of the dynamic travelling salesperson problem [research frontier], 2020

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First computed 2026-05-17T23:39:19.319683Z
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Aliases

arxiv: 2605.13871 · arxiv_version: 2605.13871v1 · doi: 10.48550/arxiv.2605.13871 · pith_short_12: HNXHZH2PXFNU · pith_short_16: HNXHZH2PXFNUBHKI · pith_short_8: HNXHZH2P
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