Constraint satisfaction problems (CSPs) sometimes contain both variable symmetries and value symmetries, causing adverse effects on CSP solvers based on tree search. As a remedy, symmetry breaking constraints are commonly used. While variable symmetry breaking constraints can be expressed easily and propagated efficiently using lexicographic ordering, value symmetry breaking constraints are often difficult to formulate. In this paper, we propose two methods of using symmetry breaking constraints to tackle value symmetries. First, we show theoretically when value symmetries in one CSP correspond to variable symmetries in another CSP of the same problem. We also show when variable symmetry breaking constraints in the two CSPs, combined using channeling constraints, are consistent. Such results allow us to tackle value symmetries efficiently using additional CSP variables and channeling constraints. Second, we introduce value precedence, a notion which can be used to break a common class of value symmetries, namely symmetries of indistinguishable values. While value precedence can be expressed using inefficient ifthen constraints in existing CSP solvers, we propose efficient propagation algorithms for implementing global value precedence constraints. We also characterize several theoretical properties of the value precedence constraints. Extensive experiments are conducted to verify the feasibility and efficiency of the two proposals. 1.

In this paper we describe the problem of Optimal Competitive Scheduling, which consists of activities that compete for a shared resource. The objective is to choose a subset of activities to schedule, sequence them, and decide how much time they are allowed, in such a way that temporal and resource constraints are satisfied and overall schedule quality is maximized. While most such problems are N P-complete, very restricted versions of this problem are known to be tractable. In this work we describe tractable variations on this problem that correspond to realistic scheduling problems. The first class of tractable OCS problems arises due to limitations on the objective function that permit casting the problem as a Linear Program; with one additional assumption on activity feasibility windows, we identify a problem class where an optimal activity ordering can be found in polynomial time. The second class arises by reformulation of the problem as a Valued Constraint Satisfaction Problem and exploiting known results on tractability. We describe implementations of specialpurpose algorithms designed to solve tractable OCS problems, and identify different solver performance characteristics based on properties of the problem instances.