Alexei Barbosa de Aguiar

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The Generate-and-Solve (GS) methodology is a hybrid method that combines a metaheuristic component with an exact solver. GS has been recently introduced in the literature in order to solve cutting and packing problems, showing promising results. The GS framework includes a metaheuristic engine (e.g., a genetic algorithm) that works as a generator of reduced(More)
This paper presents an applicability analysis over a novel integer programming model devoted to optimize power consumption efficiency in heterogeneous wireless sensor networks. This model is based upon a schedule of sensor allocation plans in multiple time intervals subject to coverage and connectivity constraints. By turning off a specific set of redundant(More)
High power consumption efficiency in wireless sensor networks is always desirable. One way to deal with this issue is using a linear integer programming model based upon a schedule of sensor allocation plans in multiple time intervals subject to coverage and connectivity constraints. The Generate-and-Solve (GS) methodology is a hybrid approach that combines(More)
The integrative collaboration of genetic algorithms and integer linear programming as specified by the Generate and Solve methodology tries to merge their strong points and has offered significant results when applied to wireless sensor networks domains. The Generate and Solve (GS) methodology is a hybrid approach that combines a metaheuristics component(More)
GSM networks are very expensive. The network design process requires too many decisions in a combinatorial explosion. For this reason, the larger is the network, the harder is to achieve a totally human based optimized solution. The BSC (Base Station Control) nodes have to be geographically well allocated to reduce the transmission costs. There are(More)
GSM Network Designs usually offers big challenges for achieving an efficient cost while respecting the complex combinatorial technical constraints. This networks have hundred or thousands BTS. They have their traffic grouped in hubs, then in BSC nodes to reach the MSC. Hubs must be elected within the BTS set and BSC nodes have to be geographically allocated(More)
GSM Network Designs usually offers big challenges for achieving an efficient cost while respecting the complex combinatorial technical constraints. This networks have hundreds or thousands BTS (Base Transceiver Station). They have their traffic grouped in hubs, then in BSC (Base Station Controller) nodes to reach the MSC. Hubs must be elected within the BTS(More)
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