Multi-Agent Parallel Implementation To Solve Nonlinear Equality Constrained Multiobjective Optimization Problem - Case of Unmanned Aerial Vehicle (UAV)

This paper investigates a decomposition-coordination method using Multi-agent systems implementation for solving the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in a conflicting situation. A practical case...

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Vydáno v:2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS) s. 1 - 6
Hlavní autoři: Jaafar, Adil, Illoussamen, Youssef, Vrochidou, Eleni, Pachidis, Theodore, Kaburlasos, Vassilis G., Mestari, Mohammed
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2019
Témata:
Complex systems
Containers
decomposition-coordination
Linear programming
Multi-Agent
Multi-agent systems
NECMOP
Neural networks
Optimization
UAV
Unmanned aerial vehicles
Unmanned Aerial Vehicule
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Shrnutí:This paper investigates a decomposition-coordination method using Multi-agent systems implementation for solving the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in a conflicting situation. A practical case study of an unmanned aerial vehicle was found to fit the characteristics of the model and was then taken to test the effectiveness of the method. The NECMOP is converted to an equivalent scalar optimization problem (SOP) which is then decomposed into several separable subproblems. These latter are independent from each other, which makes them processable in parallel and allows nonlinearity to be treated at a local level by an agent which lives in a container. The agents communicate the results to the master agent who coordinates the intermediate solutions using Lagrange multipliers and requests a new loop until it finds an optimal solution that satisfies all the constraints.
DOI:10.1109/ICDS47004.2019.8942338