Greedy Algorithm for Multiway Matching with Bounded Regret

A Unified View of Online Matching and Resource Allocation Problems Whereas small regret online algorithms for applications as diverse network revenue management (NRM), assemble-to-order (ATO) systems, stochastic bin packing (SBP) are known in the literature, design existing tailored to specific application often use strategy resolving a planning linear program. In paper “Greedy Algorithm Multiway with Bounded Regret,” Gupta proposes unified model studying such matching/allocation problems. model, resources three types—off-line (e.g., inventory NRM), online-queueable orders or ATO systems), online-nonqueueable requests NRM, items SBP)—must be combined create feasible configurations. Leveraging framework, author gives one simple greedy algorithm that (bounded logarithmic time horizon) these under mild nondegeneracy condition on off-line problem.