Empirical Studies of Heuristic Local Search for Constraint Solving

Abstract

. The goal of this paper is twofold. First, we introduce a class of local search procedures for solving optimization and constraint problems. These procedures are based on various heuristics for choosing variables and values in order to examine a general neighborhood. Second, four combinations of heuristics are empirically evaluated by using the graph-coloring problem and a real world application - the frequency assignment problem. The results are also compared with those obtained with other approaches including simulated annealing, Tabu search, constraint programming and heuristic graph coloring algorithms. Empirical evidence shows the benefits of this class of local search procedures for solving large and hard instances. Keywords: Local search, constraint solving, combinatorial optimization, graph coloring, frequency assignment. 1 Introduction Constraint problems embodies a class of general problems which are important both in theory and in practice. Well-known examples include con..