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M. Toleubek

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Open access Sep 2026

DISTRIBUTIONALLY ROBUST HAMILTONIAN CYCLE OPTIMIZATION ON STOCHASTIC GRAPHS VIA WASSERSTEIN-METRIC GENETIC ALGORITHMS: EMPIRICAL EVIDENCE FROM ALMATY AND ASTANA

This paper introduces a data-driven Distributionally Robust Optimization (DRO) framework to identify risk-averse Hamiltonian cycles in non-stationary stochastic networks subject to severe probabilistic uncertainty. Rather than relying on static nominal travel times, which suffer heavily from the optimizer's curse, we c...

Аббасов Зафар Думан, M. Toleubek, T. Z. Yelemes · 0 citations

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