Abstract We consider the following control problem on fair allocation of indivisible goods. Given a set I of items and a set of agents, each having strict linear preferences over the items, we ask for a minimum subset of the items whose deletion guarantees the existence of a proportional allocation in the remaining instance; we call this problem Proportionality by Item Deletion (PID). Our main result is a polynomial-time algorithm that solves PID for three agents. By contrast, we prove that PID is computationally intractable when the number of agents is unbounded, even if the number k of item deletions allowed is small—we show that the problem is $${\mathsf {W}}[3]$$ W [ 3 ] -hard with respect to the parameter k. Additionally, we provide some tight lower and upper bounds on the complexity of PID when regarded as a function of |I| and k. Considering the possibilities for approximation, we prove a strong inapproximability result for PID. Finally, we also study a variant of the problem where we are given an allocation $$\pi $$ π in advance as part of the input, and our aim is to delete a minimum number of items such that $$\pi $$ π is proportional in the remainder; this variant turns out to be $${{\mathsf {N}}}{{\mathsf {P}}}$$ N P -hard for six agents, but polynomial-time solvable for two agents, and we show that it is $$\mathsf {W[2]}$$ W [ 2 ] -hard when parameterized by the number k of

Combinatorial auctions are mechanisms for allocating bundles of goods to agents who each have preferences over these goods. Finding an economically efficient allocation, the so-called winner determination problem, is computationally intractable in the general case, which is why it is important to identify special cases that are tractable but also sufficiently expressive for applications. We introduce a family of auction problems in which the goods on auction can be rearranged into a sequence, and each bid submitted concerns a bundle of goods corresponding to an interval on this sequence, possibly with multiple gaps of bounded length. We investigate the computational complexity of the winner determination problem for such auctions and explore the frontier between tractability and intractability in detail, identifying tractable, intractable, and fixed-parameter tractable cases.

We study the complexity of the destructive bribery problem (an external agent tries to prevent a disliked candidate from winning by bribery actions) in voting over combinatorial domains, where the set of candidates is the Cartesian product of several issues. This problem is related to the concept of the margin of victory of an election which constitutes a measure of robustness of the election outcome and plays an important role in the context of electronic voting. In our setting, voters have conditional preferences over assignments to these issues, modelled by CP-nets. We settle the complexity of all combinations of this problem based on distinctions of four voting rules, five cost schemes, three bribery actions, weighted and unweighted voters, as well as the negative and the non-negative scenario. We show that almost all of these cases are $$\mathcal {NP}$$ -complete or $$\mathcal {NP}$$ -hard for weighted votes while approximately half of the cases can be solved in polynomial time for unweighted votes.