This article explores the application of evolutionary algorithms and agent-oriented programming to solve the problem of searching and monitoring objectives through a fleet of unmanned aerial vehicles. The subproblem o...
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ISBN:
(纸本)9783030410056;9783030410049
This article explores the application of evolutionary algorithms and agent-oriented programming to solve the problem of searching and monitoring objectives through a fleet of unmanned aerial vehicles. The subproblem of static off-line planning is studied to find initial flight plans for each vehicle in the fleet, using evolutionary algorithms to achieve compromise values between the size of the explored area, the proximity of the vehicles, and the monitoring of points of interest defined in the area. The results obtained in the experimental analysis on representative instances of the surveillance problem indicate that the proposed techniques are capable of computing effective flight plans.
One of the possible ways to increase the end-to-end power transfer efficiency in a radiative Wireless Power Transfer (WPT) system is by transmitting multi-tone signals optimized according to the receiver rectenna'...
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ISBN:
(纸本)9781728166872
One of the possible ways to increase the end-to-end power transfer efficiency in a radiative Wireless Power Transfer (WPT) system is by transmitting multi-tone signals optimized according to the receiver rectenna's nonlinear behavior and the Channel State Information (CSI). This optimization problem is a non-convex problem that has been tackled in the past with Sequential Convex Programming (SCP) algorithms. Since SCP algorithms do not guarantee to track the globally optimal solutions, there is interest in applying some other optimization methods to this problem. Here we apply various evolutionary algorithms (EAs) with different characteristics. The performance of the designed waveforms is evaluated in Matlab, using a simplified Single Input Single Output (SISO) system model. EAs are successfully applied to waveform design for WPT and seem to track the optimal solutions in the tested cases. Moreover, the effectiveness of the SCP-QCLP method is verified.
evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatorial optimization problems, often more ...
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ISBN:
(纸本)9781450371285
evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatorial optimization problems, often more knowledge about the structure of optimal solutions is given, which can be leveraged by means of biased search operators. We consider the Minimum Spanning Tree (MST) problem in a single- and multi-objective version, and introduce a biased mutation, which puts more emphasis on the selection of edges of low rank in terms of low domination number. We present example graphs where the biased mutation can significantly speed up the expected runtime until (Pareto-)optimal solutions are found. On the other hand, we demonstrate that bias can lead to exponential runtime if "heavy" edges are necessarily part of an optimal solution. However, on general graphs in the single-objective setting, we show that a combined mutation operator which decides for unbiased or biased edge selection in each step with equal probability exhibits a polynomial upper bound - as unbiased mutation - in the worst case and benefits from bias if the circumstances are favorable.
It has been shown before that some results from the theory of evolutionary algorithms (EAs) may be used for the analysis of population dynamics in biology. In the present paper, we study the EAs without elite individu...
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Many real-world optimisation problems involve dynamic and stochastic components. While problems with multiple interacting components are omnipresent in inherently dynamic domains like supply-chain optimisation and log...
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evolutionary algorithms (EAs) are widely used for optimization. Their use is particularly beneficial for problems where underlying objective functions and/or constraints are highly non-linear / black-box and the class...
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One of the challenges that appear in solving constrained optimization problems is to quickly locate the search areas of interest. Although the initial solutions of any optimization algorithm have a significant effect ...
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Previously a theoretical study of the average convergence rate was conducted for discrete optimisation. This paper extends it to a further analysis for continuous optimisation. First, the strategies of generating new ...
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As the availability of high-performance computing systems rises to unprecedented levels in the exascale era, vastly scalable parallelism is now an accessible, viable option for a wide range of scientific fields and al...
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Multiple gravity assist (MGA) trajectories represent a particular class of space trajectories in which a spacecraft makes use of gravity assist (GA) of one or more celestial bodies to alter its path or velocity vector...
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