This paper presents a new approach for parallel heuristic algorithms based on adaptive parallelism. Adaptive parallelism was used to dynamically adjust the parallelism degree of the application with respect to the system load. This approach demonstrates that high-performance computing using heterogeneous workstations combined with massively parallel machines is feasible to solve large assignment problems. The fault-tolerant algorithm allows a minimal loss of computation in case of failures. The proposed algorithm exploits the properties of this class of applications in order to reduce the complexity of the algorithm. The parallel heuristic algorithm combines different search strategies: simulated annealing and tabu search. Encouraging results have been obtained in solving the quadratic assignment problem. We have improved the best known solutions for some large real-world problems.
CITATION STYLE
Talbi, E. G., Geib, J. M., Hafidi, Z., & Kebbal, D. (1998). A fault-tolerant parallel heuristic for assignment problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1388, pp. 306–314). Springer Verlag. https://doi.org/10.1007/3-540-64359-1_701
Mendeley helps you to discover research relevant for your work.