Towards Aid by Generate and Solve Methodology: Application in the Problem of Coverage and Connectivity in Wireless Sensor Networks. (24th October 2012)

• Record Type: Journal Article
• Authors: Pinheiro, Placido Rogerio; Coelho, Andre Luis Vasconcelos; Aguiar, Alexei Barbosa; Sobreira Neto, Alvaro de Menezes
• Other Names: Lin Shan Academic Editor.
• Is Part Of: International journal of distributed sensor networks. (2012)
• Publication Date: 2012-10-24
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2012/790459
• Languages: English
• ISSNs: 1550-1329

Abstract

Abstract : 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 with an exact solver. GS has been recently introduced into the literature in order to solve the problem of dynamic coverage and connectivity in wireless sensor networks, showing promising results. The GS framework includes a metaheuristics engine (e.g., a genetic algorithm) that works as a generator of reduced instances of the original optimization problem, which are, in turn, formulated as mathematical programming problems and solved by an integer programming solver.