Polynomial Silent Self-Stabilizing p-Star Decomposition

We present a silent self-stabilizing distributed algorithm computing a maximal p-star decomposition of the underlying communication network. Under the unfair distributed scheduler, the most general scheduler model, the algorithm converges in at most 12∆m + O(m + n) moves, where m is the number of edges, n is the number of nodes, and ∆ is the maximum node degree. Regarding the move complexity, our algorithm outperforms the previously known best algorithm by a factor of ∆. While the round complexity for the previous algorithm was unknown, we show a 5 [n/(p+1)] + 5 bound for our algorithm

A Grid-based Parallel Approach of the Multi-Objective Branch and Bound

International audienceThe branch and bound (B&B) algorithm is one of the most used methods to solve in an exact way combinatorial optimization problems. This article focuses on the multi-objective version of this algorithm, and proposes a new parallel approach adapted to grid computing systems. This approach addresses several issues related to the characteristics of the algorithm itself and the properties of grid computing systems. Validation is performed by experimenting the approach on a bi-objective flow-shop problem instance that has never been solved exactly. Solving this instance, after several days of computation on a grid of more than 1000 processors, belonging to 7 distinct clusters, the obtained results prove the efficiency of the proposed approac