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In recent years the unconstrained binary quadratic program (UBQP) has grown in importance in the field of combinatorial optimization due to its application potential and its computational challenge. Research on UBQP has generated a wide range of solution techniques for this basic model that encompasses a rich collection of problem types. In this paperwe(More)
Graph partitioning is one of the most studied NPcomplete problems. Given a graph G = (V, E), the task is to partition the vertex set V into k disjoint subsets of about the same size, such that the number of edges with endpoints in different subsets is minimized. In this work, we present a highly effective multilevel memetic algorithm, which integrates a new(More)
This paper presents a multi-objective local search, where the selection is realized according to the hypervolume contribution of solutions. The HBMOLS algorithm proposed is inspired from the IBEA algorithm, an indicator-based multi-objective evolutionary algorithm proposed by Zitzler and Künzli in 2004, where the optimization goal is defined in terms of a(More)
This paper presents a study of Evolutionary Algorithms (EAs) for a real application: the Frequency Assignment Problem (FAP) in Cellular Radio Networks. This problem is of great importance both in practice and in theory. In practice, solving this problem eeciently will allow the telecommunications operator to manage larger and larger cellular networks. In(More)
In this paper, a simulated annealing algorithm is presented for the bandwidth minimization problem for graphs. This algorithm is based on three distinguished features including an original internal representation of solutions, a highly discriminating evaluation function and an effective neighborhood. The algorithm is evaluated on a set of 113 well-known(More)
In this paper, we present a general approach for solving constraint problems by local search. The proposed approach is based on a set of high-level constraint primitives motivated by constraint programming systems. These constraints constitute the basic bricks to formulate a given combinatorial problem. A tabu search engine ensures the resolution of the(More)
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, we introduce the following clustering hypothesis: the high quality solutions are not randomly scattered in the search space, but rather grouped in clusters within spheres of(More)
The quadratic assignment problem (QAP) is one of the most studied NPhard problems with various practical applications. In this work, we propose a powerful population-based memetic algorithm (called BMA) for QAP. BMA integrates an effective local optimization algorithm called Breakout Local Search (BLS) within the evolutionary computing framework which(More)
The quadratic assignment problem (QAP) is one of the most studied combinatorial optimization problems with various practical applications. In this paper, we present Breakout Local Search (BLS) for solving QAP. BLS explores the search space by a joint use of local search and adaptive perturbation strategies. Experimental evaluations on the set of QAPLIB(More)