Abstract. Many real world problems, e.g. personnel scheduling and transportation planning, can be modeled naturally as Constrained Shortest Path Problems (CSPPs), i.e., as Shortest...
Knapsack constraints are a key modeling structure in discrete optimization and form the core of many real-life problem formulations. Only recently, a cost-based filtering algorit...
Incomplete decision algorithms can often solve larger problem instances than complete ones. The drawback is that one does not know whether the algorithm will finish soon, later, ...
Mechanism design is the art of designing the rules of the game (aka. mechanism) so that a desirable outcome (according to a given objective) is reached despite the fact that each a...
This paper aims to show that Constraint Programming can be an efficient technique to solve a well-known combinatorial optimization problem: the search for a maximum clique in a gra...
Multiple sequence alignment is a central problem in Bioinformatics. A known integer programming approach is to apply branch-and-cut to exponentially large graph-theoretic models. T...
Steven David Prestwich, Desmond G. Higgins, Orla O...
Symmetry in a Constraint Satisfaction Problem can cause wasted search, which can be avoided by adding constraints to the CSP to exclude symmetric assignments or by modifying the s...
This paper presents two methods for improving the performance of the Distributed Breakout Algorithm using the notion of interchangeability. In particular, we use neighborhood part...