Online Combinatorial Assignment in Independence Systems
Javier Marinkovic, Jos\'e A. Soto, Victor Verdugo

TL;DR
This paper advances online combinatorial assignment algorithms by providing improved competitiveness bounds and polynomial-time solutions for various independence systems, including hypergraph matchings and matroids, in multiple stochastic models.
Contribution
It introduces exponential improvements in competitiveness bounds for online algorithms in independence systems and develops new polynomial-time algorithms using linear programming techniques.
Findings
Upper bounds of O(log(k)/k) and O(log(n)/√n) on competitiveness.
New algorithms with competitive ratios like (1-e^{-k})/k and 1/(k+1).
Polynomial-time algorithms for matroids, matroid intersections, and matchoids.
Abstract
We consider an online multi-weighted generalization of several classic online optimization problems, called the online combinatorial assignment problem. We are given an independence system over a ground set of elements and agents that arrive online one by one. Upon arrival, each agent reveals a weight function over the elements of the ground set. If the independence system is given by the matchings of a hypergraph we recover the combinatorial auction problem, where every node represents an item to be sold, and every edge represents a bundle of items. For combinatorial auctions, Kesselheim et al. showed upper bounds of O(loglog(k)/log(k)) and on the competitiveness of any online algorithm, even in the random order model, where is the maximum bundle size and is the number of items. We provide an exponential improvement on these upper bounds to show that…
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Taxonomy
TopicsOptimization and Search Problems · Auction Theory and Applications · Complexity and Algorithms in Graphs
