Solving Multi-Configuration Problems: A Performance Analysis with Choco Solver
This addresses the need for efficient multi-configuration in scenarios like personalized exams, but it appears incremental as it focuses on performance analysis of an existing solver.
The paper tackles the problem of multi-configuration, where multiple personalized solutions are generated simultaneously, by applying it to individualized exam generation and analyzing performance using the Choco constraint solver.
In many scenarios, configurators support the configuration of a solution that satisfies the preferences of a single user. The concept of \emph{multi-configuration} is based on the idea of configuring a set of configurations. Such a functionality is relevant in scenarios such as the configuration of personalized exams, the configuration of project teams, and the configuration of different trips for individual members of a tourist group (e.g., when visiting a specific city). In this paper, we exemplify the application of multi-configuration for generating individualized exams. We also provide a constraint solver performance analysis which helps to gain some insights into corresponding performance issues.