Online submodular maximization with preemption

Niv Buchbinder, Moran Feldman, Roy Schwartz

Research output: Contribution to journalArticlepeer-review


Submodular function maximization has been studied extensively in recent years under various constraints and models. The problem plays a major role in various disciplines. We study a natural online variant of this problem in which elements arrive one by one and the algorithm has to maintain a solution obeying certain constraints at all times. Upon arrival of an element, the algorithm has to decide whether to accept the element into its solution and may preempt previously chosen elements. The goal is tomaximize a submodular function over the set of elements in the solution. We study two special cases of this general problem and derive upper and lower bounds on the competitive ratio. Specifically, we design a 1/e-competitive algorithm for the unconstrained case in which the algorithm may hold any subset of the elements, and constant competitive ratio algorithms for the case where the algorithm may hold at most k elements in its solution.

Original languageEnglish
Article number0076
JournalACM Transactions on Algorithms
Issue number3
StatePublished - May 2019


FundersFunder number
USIsrael BSF2014414
European Research Council1357/16, 1336/16, 335288-OptApprox
Israel Science Foundation1585/15


    • Competitive analysis
    • Online algorithms
    • Preemption
    • Submodular maximization


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