Bendjoudi, AhcèneMelab, NouredineTalbi, El-Ghazali2013-06-122013-06-122009http://dl.cerist.dz/handle/CERIST/192Solving optimally large instances of combinatorial optimisation problems using Branch and Bound (B&B) algorithms is CPU-time intensive and requires a large number of computational resources. To harness such huge amount of resources Peer-to-Peer (P2P) communications must be allowed between resources, and adaptive load balancing and fault-tolerance have to be dealt with when designing and implementing a B&B algorithm. In this paper, we propose a P2P design and implementation of a parallel B&B algorithm on top of the ProActive grid middleware. Load distribution and fault-tolerance strategies are proposed to deal with the dynamic and heterogeneous characteristics of the computational grid. The approach has been promisingly applied to the Flow-Shop scheduling problem and experimented on a computational pool of 1500 CPUs from the GRID’5000 Nation-wide experimental Grid.combinatorial optimisation; permutation flow-shop problem; parallel branch and bound; peer-to-peer computing; ProActive.ArticleInderscience Enterprises Ltd