In this paper, the NP-hard problem of minimizing power consumption in wireless communications systems is approached. In the literature, several metaheuristic approaches have been proposed to solve it. Currently a homo...
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In this paper, the NP-hard problem of minimizing power consumption in wireless communications systems is approached. In the literature, several metaheuristic approaches have been proposed to solve it. Currently a homogeneous cellularprocessing algorithm and a GRASP algorithm hybridized with path-relinking are considered the state of the art algorithms. The main contribution of this paper is the analysis of five main characteristics for a heterogeneous cellularprocessing algorithm, based on scatter search and GRASP. A series of computational experiments with standard instances were carried out to assess the impact of each one of these characteristics. Among the main analyses we found particularly interesting a time reduction by 74.24 %, produced by the stagnation detection characteristic. Also the communication characteristic improves the quality of the solutions by 24.73 %. The computational results show that our heterogeneous cellularprocessing algorithm is a good alternative for solving the problem. The proposed algorithm finds 34 new best known solutions, which is 27 % of the instances with unknown optimal values. A Friedman hypothesis test was carried out to validate that two state-of-the-art algorithms and the proposed algorithm are statistically equivalent.
The vertex bisection problem splits a graph G = (V, E) into two sets, L subset of V, vertical bar L vertical bar left perpendicular vertical bar V vertical bar/2 right perpendicular and R = V \ L, such that it minimiz...
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The vertex bisection problem splits a graph G = (V, E) into two sets, L subset of V, vertical bar L vertical bar left perpendicular vertical bar V vertical bar/2 right perpendicular and R = V \ L, such that it minimizes the number of vertices in L connected to R. This problem is a combinatorial NP-hard problem with relevant applications in network communications and, currently, there is only one metaheuristic method that solves it. In this paper, we propose a cellularprocessing Algorithm (CPA) that outperforms the state of the art showing a detailed description of its components and assessing the impact of its main components. Additionally, we include the best-known solutions for the new benchmark of 137 challenging instances. The experimental study, with the new benchmark, shows that the CPA increases the number of best solutions found to 190% and decreases the time to 21% with respect to an efficiency-improved version of the state of the art algorithm. Finally, a non-parametric statistical hypothesis test confirms that the CPA outperforms statistically the efficiency-improved implementation of the state of the art algorithm. (C) 2018 Elsevier Inc. All rights reserved.
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