feat: Rao family extensions v0.10.0 — BMWR + MO-* + self-adaptive variants#1
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…iants Python wrappers and Rust bindings for 7 new solvers from Prof. R.V. Rao's 2025–2026 papers (Metals 15/9/1057, Energies 19/1/34, JMMP 9/8/249) and related self-adaptive variants. New Python entry points (rao_algorithms.*): - BMWR_algorithm — Best-Mean-Worst-Random (Rao 2025) - SAMP_Jaya_algorithm — Self-Adaptive Multi-Population Jaya (2017) - EHRJaya_algorithm — Hybrid Jaya + Rao-1 (EAAI 2022) - QO_Rao_algorithm — Quasi-Oppositional Rao (JCDE 2020) New Rust bindings (samyama_optimization.*): - solve_bmwr, solve_samp_jaya, solve_ehrjaya, solve_qo_rao, solve_saphr - solve_mo_bmr, solve_mo_bwr, solve_mo_bmwr, solve_mo_rao_de (with PyMultiObjectiveResult / PyMultiObjectiveIndividual classes) Version bumps: - rao-algorithms (pip): 0.9.3 → 0.10.0 - samyama-optimization-python (Rust crate): 0.9.3 → 0.10.0 - Depends on samyama-optimization crate v1.1.0 (samyama-graph PR #174) Docs: docs/algorithms/bmwr.md, docs/algorithms/mo_bmwr_family.md; updated docs/references/rao_publications.md with 2025–2026 MO papers and implemented self-adaptive variants list.
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Summary
rao-algorithms0.9.3 → 0.10.0;samyama-optimization-python0.9.3 → 0.10.0.samyama-optimizationcrate v1.1.0 (feat(optimization): Rao family extensions — BMWR + MO-* + self-adaptive variants samyama-graph#174).New Python entry points
BMWR_algorithm,SAMP_Jaya_algorithm,EHRJaya_algorithm,QO_Rao_algorithm.New Rust bindings
Single-objective:
solve_bmwr,solve_samp_jaya,solve_ehrjaya,solve_qo_rao,solve_saphr.Multi-objective:
solve_mo_bmr,solve_mo_bwr,solve_mo_bmwr,solve_mo_rao_dewithPyMultiObjectiveResult/PyMultiObjectiveIndividual.Papers implemented
Test plan
maturin develop) lights up the new Python entry points end-to-end