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      Genetic algorithm-based multiple moving target reaching using a fleet of sailboats

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          Abstract

          This study addresses the problem of Dynamic Travelling Salesman Problem for a multi-agent system using a fleet of sailboats. A genetic algorithm (GA) is proposed, which attributes to each agent a varying number of targets to be collected. GA allows obtaining a suboptimal solution in the shortest time possible. Moreover, this study adapts it to the specific problem involving a fleet of sailboats, which is a challenging task with comparison to autonomous underwater vehicles or motorised vehicles in terms of the propulsion. Therein motors can be flexibly controlled while sailboat movements are constrained by available wind direction and speed. Thus the method takes into account wind conditions at various locations of the sailboat. Simulation results demonstrate the effectiveness of the proposed approach.

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          Most cited references 14

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          On the Predictability of Lagrangian Trajectories in the Ocean

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            Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace.

             Daqi Zhu,  Huan Huang,  S. Yang (2013)
            For a 3-D underwater workspace with a variable ocean current, an integrated multiple autonomous underwater vehicle (AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach. The goal is to control a team of AUVs to reach all appointed target locations for only one time on the premise of workload balance and energy sufficiency while guaranteeing the least total and individual consumption in the presence of the variable ocean current. First, the SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in 3-D ocean environment. The working process involves special definition of the initial neural weights of the SOM network, the rule to select the winner, the computation of the neighborhood function, and the method to update weights. Then, the velocity synthesis approach is applied to plan the shortest path for each AUV to visit the corresponding target in a dynamic environment subject to the ocean current being variable and targets being movable. Lastly, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper.
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              Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems

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                Author and article information

                Contributors
                Journal
                IET-CSR
                IET Cyber-systems and Robotics
                IET Cyber-syst. Robot.
                The Institution of Engineering and Technology
                2631-6315
                11 November 2019
                12 December 2019
                December 2019
                : 1
                : 3
                : 93-100
                Affiliations
                [1 ] School of Engineering, Computing and Mathematics, University of Plymouth , Plymouth, Devon, UK
                [2 ] Lab STICC, ENSTA Bretagne , Brest, France
                Article
                IET-CSR.2019.0029 CSR.2019.0029.R1
                10.1049/iet-csr.2019.0029

                This is an open access article published by the IET and Zhejiang University Press under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                Page count
                Pages: 0
                Product
                Funding
                Funded by: Engineering and Physical Sciences Research Council
                Award ID: EP/R005532/1
                Categories
                Research Article

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