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The clustering problem is among the most important optimization problems. Given that it is an NP-hard problem, it can be efficiently solved using meta-heuristic algorithms such as the gravitation search algorithm (GSA). GSA is a new swarm- based algorithm particularly suitable for solving NP-hard combinatorial optimization problems. This paper solves the clustering problem with a newly proposed memetic...
Graph partitioning is one of the most studied NP-complete problems. Given a graph , the task is to partition the vertex set into disjoint subsets of about the same size, such that the number of edges with endpoints in different subsets is minimized. In this paper, we present a highly effective multilevel memetic algorithm, which integrates a new multiparent crossover operator and a powerful...
The balanced graph partitioning consists in dividing the vertices of an undirected graph into a given number of subsets of approximately equal size, such that the number of edges crossing the subsets is minimized. In this work, we present a multilevel memetic algorithm for this NP-hard problem that relies on a powerful grouping recombination operator and a dedicated local search procedure. The proposed...
Circuit-partitioning is one of the most important, but time-consuming steps, in the VLSI design flow. In this paper, we investigate six different parallel Memetic Algorithms for solving the circuit-partitioning problem. Each parallel implementation uses a global shared-memory to exchange information, and seeks to reduce runtime by exploiting the multiple cores available in today's commodity hardware...
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