Section: New Results

New data structure for solving large permutation problems using multi-core B&B

Participants : Rudi Leroy, Nouredine Melab.

Solving large permutation problems using parallel B&B algorithms results in the generation of a very large pool of subproblems. Defining an efficient data structure is highly required to store and manage efficiently that pool. In [31] , we have proposed a new dedicated data structure called Integer-Vector-Matrix (or IVM and redefined the operators of the B&B algorithm acting on it. We have also revisited the Work Stealing mechanism on multi-core processors. In the proposed approach, work units are coded in a coalesced way using factoradic-based intervals, and private IVMs are used to store and explore locally subsets of subproblems. The IVM-based approach has been experimented and compared to the approach based on concurrent linked-list, which is often used. The results show that our approach is more efficient in terms of memory usage and management time. In [31] , we have investigated various work stealing strategies based on different victim selection and granularity policies. This later paper has been selected for a special issue in the CCPE international journal.