Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
A multi-objective probabilistic forecast combination framework is introduced that generates Pareto-optimal combinations balancing forecast accuracy and inventory decision performance, outperforming single-objective methods on retail and spare parts data.
An additive model separates ranking information from scale variation in noisy non-reciprocal pairwise comparisons and derives noise estimators plus ranking-region probabilities.
citing papers explorer
-
Multi-objective probabilistic forecast combination for inventory demand
A multi-objective probabilistic forecast combination framework is introduced that generates Pareto-optimal combinations balancing forecast accuracy and inventory decision performance, outperforming single-objective methods on retail and spare parts data.