GENET and Tabu Search for Combinatorial Optimization Problems

Constraint satisfaction problems are combinatorial optimization problems which involve finding an assignment to a set of variables that is consistent with a set of constraints. In this paper the use of two local search techniques, namely GENET and Tabu Search for constraint satisfaction optimization problems and partial constraint satisfaction problems is investigated. These methods are compared by application to a difficult partial constraint satisfaction optimization problem, namely the Radio Links Frequency Assignment Problem (RLFAP).