
We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and---in addition to a global budget limit---there are several groupings of the projects, each group with its own budget limit. We study the computational complexity of identifying project bundles that maximize voter satisfaction while respecting all budget limits. We show that the problem is generally intractable and describe efficient exact algorithms for several special cases, including instances with only few groups and instances where the group structure is close to being hierarchical, as well as efficient approximation algorithms. Our results could allow, e.g., municipalities to hold richer PB processes that are thematically and geographically inclusive.
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Artificial Intelligence (cs.AI), Computer Science - Computer Science and Game Theory, 68Q17, 68Q25, 68W05 (Primary), 68W25, 68T42 (Secondary), Computer Science - Data Structures and Algorithms, Computer Science - Multiagent Systems, Data Structures and Algorithms (cs.DS), F.2.2, Computer Science and Game Theory (cs.GT), Multiagent Systems (cs.MA)
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Artificial Intelligence (cs.AI), Computer Science - Computer Science and Game Theory, 68Q17, 68Q25, 68W05 (Primary), 68W25, 68T42 (Secondary), Computer Science - Data Structures and Algorithms, Computer Science - Multiagent Systems, Data Structures and Algorithms (cs.DS), F.2.2, Computer Science and Game Theory (cs.GT), Multiagent Systems (cs.MA)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
