Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/6254
Title: Using evolutionary algorithms to plan automatic minehunting operations
Authors: Nuno Miguel Abreu
Aníbal Matos
Issue Date: 2014
Abstract: While autonomous underwater vehicles (AUVs) are increasingly being used to perform mine countermeasures (MCM) operations, the capability of these systems is limited by the efficiency of the planning process. In this paper we study the problem of multiobjective MCM mission planning with an AUV. In order to overcome the inherent complexity of the problem, a multi-stage algorithm is proposed and evaluated. Our algorithm combines an evolutionary algorithm (EA) with a local search procedure based on simulated annealing (SA), aiming at a more flexible and effective exploration and exploitation of the search space. An artificial neural network (ANN) model was also integrated in the evolutionary procedure to guide the search. The results show that the proposed strategy can efficiently identify a higher quality solution set and solve the mission planning problem.
URI: http://repositorio.inesctec.pt/handle/123456789/6254
http://dx.doi.org/10.5220/0005043102280235
metadata.dc.type: conferenceObject
Publication
Appears in Collections:CRAS - Articles in International Conferences

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