Parallel Skeletons for Tabu Search Method

In this paper we present two generic parallel skeletons for Tabu Search method –a well known meta-heuristic for approximately solving combinatorial optimization problems. The first skeleton is based on independent runs while the second in the classical master-slave model. Our starting point is the design and implementation of a sequential skeleton that is used later as basis for the two parallel skeletons. Both skeletons provide the user with the followings: (a) permit to obtain parallel implementations of Tabu Search method for concrete combinatorial optimization problems from existing sequential implementations; (b) there is no need for the user to know neither parallel programming nor communication libraries; (c) the parallel implementation of Tabu Search for a concrete problem is obtained automatically from a sequential implementation of Tabu Search for the problem. The skeletons, however, require from the user a sequential instantiation of Tabu Search method for the problem at hand. The skeletons are implemented in C++ using MPI as communication library and offer genericity, flexibility, component reuse, robustness and time savings. We have instantiated the two skeletons for the 0-1 Multidimensional Knapsack problem, among others, for which we report com-