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arXiv AI By Hari Mohan Pandey

Coronavirus Optimization Algorithm: A Success-History Adaptive Evolutionary Framework with Archive-Assisted Search and Stagnation Recovery for Global Optimization

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The paper introduces the Coronavirus Optimization Algorithm (COA), a SARS‑CoV‑2 inspired evolutionary optimizer for box‑constrained continuous global optimization. COA maps coronavirus mechanisms to search operators such as elite‑guided attraction, trial‑vector generation, adaptive parameter variation, stagnation recovery, and population‑size scheduling, and incorporates opposition‑based initialization, current‑to‑pbest mutation, binomial crossover, an external archive, success‑history adaptation, population reduction, and partial restart. Evaluated on 29 CEC 2017 benchmark functions at 10, 30, and 50 dimensions, COA achieves the best overall Friedman rank across all dimensions, excelling particularly on composition functions while noting limitations on some hybrid functions and the need for further high‑dimensional validation.

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