Approaches to Find a Near-minimal Change Solution for Dynamic CSPs

A Dynamic Constraint Satisfaction Problem (DCSP) is a sequence of static CSPs that are formed by constraint changes. In this sequence, the solution of one CSP may be invalidated by one or more constraint changes. To find a minimal change solution for that CSP with respect to the solution of the previous related CSP, a Repair-Based algorithm with Arc-Consistency (denoted as RB-AC in [4]) has been developed. However, when a new CSP is formed by adding or changing several n-ary (n ≥ 2) constraints, using RB-AC to find a minimal change solution is much harder than using a constructive algorithm to generate an arbitrary solution from scratch. The constraint propagation techniques integrated in RB-AC do not reduce its time complexity. This paper proposes two approximate algorithms to reduce the time complexity of RB-AC by relaxing the criteria of an optimal solution. The experimental results show that one of the proposed algorithms performs quite well in terms of approximation of a minimal change solution within a limited period of time.