Research Article
Multi Tier Cooperative Population Search for Continuous Black Box Optimization
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Abstract
Structured populations can combine local adaptation, information exchange and global resource allocation. We formulate Multi Tier Cooperative Population Search (MTCPS), which combines four proposal operators, per-deme recent-improvement credits, elite migration and a coordinator that retains elites and redistributes individuals. The revised specification preserves population size, distinguishes population cycles from objective calls and separates changing penalty scores from fixed-objective incumbents. The supplied main table gives MTCPS ten strict minima and two tied minima across twelve displayed cases. However, the aggregate case count, benchmark dimensions, rank sums, correction outputs and two source figures are inconsistent, so the report does not establish verified aggregate superiority. A conditional hitting proposition replaces the unsupported population-convergence argument; it requires explicit sublevel-set coverage and indefinitely continued trials. The contribution is an inspectable combination of population organization and operator allocation, with reported numerical observations preserved for reconstruction rather than certified as independently reproduced experiments.
Keywords
Structured population search Adaptive operator selection Elite migration Evaluation budgeting Conditional convergence Benchmark interpretationReferences (25)
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- Published 2026-12-07
- Issue Vol. 3 No. 4 (2026): Optimality
- Section Articles
- Document Type Research Article
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How to Cite
Marchetti, A. L. ., Zhang, B. ., Novak, J. H. ., & Cherif, A. . (2026). Multi Tier Cooperative Population Search for Continuous Black Box Optimization. Optimality, 3(4), 308-324. https://doi.org/10.22105/opt.v3i4.122