Synchronous tabu search parallelization strategies for multicommodity location-allocation with balancing requirements

We study and compare synchronous parallelization strategies for tabu search. We identify the most promising parallelization approaches, and evaluate the impact on performance and solution quality of some important algorithmic design parameters: length of the synchronization steps, number of processors, handling of exchanged information, etc. Parallelization approaches are implemented and compared by using a tabu search algorithm for multicommodity location-allocation problems with balancing requirements.