Rollout Renaissance: How Pareto-NRPA Revives Monte Carlo for Multi-Objective Optimization
Monte Carlo search algorithms rarely make the shortlist in multi-objective optimization (MOO). Traditionally, the field has belonged to evolutionary algorithms like NSGA-II and SMS-EMOA. But a paper from Paris Dauphine-PSL and Thales upends that hierarchy with an audacious twist: what if we generalized NRPA — a niche but powerful single-objective method — to handle multiple objectives, constraints, and diversity, all in one elegant framework? ...