Search results for "Optimization problem"
showing 10 items of 281 documents
A Web Application for the Remote Control of Multiple Unmanned Aerial Vehicles
2019
Unmanned Aerial Vehicles (UAVs) are receiving an increasing attention from the research and industry community, and today they are adopted for several civilian and military applications. However, state of the art technologies are still based on a single UAV either directly controlled by the human operator or supervised through the manual definition of a flight plan. As a result, scalability is still a significant limitation for such systems, especially when large areas need to be monitored. In this paper we propose a web based application for the control of multiple UAVs. The application has three layers. The first layer allows the user to remotely submit a monitoring mission through a web …
Combined Elephant Herding Optimization Algorithm with K-means for Data Clustering
2018
Clustering is an important task in machine learning and data mining. Due to various applications that use clustering, numerous clustering methods were proposed. One well-known, simple, and widely used clustering algorithm is k-means. The main problem of this algorithm is its tendency of getting trapped into local minimum because it does not have any kind of global search. Clustering is a hard optimization problem, and swarm intelligence stochastic optimization algorithms are proved to be successful for such tasks. In this paper, we propose recent swarm intelligence elephant herding optimization algorithm for data clustering. Local search of the elephant herding optimization algorithm was im…
Interactive multiobjective optimization system WWW-NIMBUS on the Internet
2000
Abstract NIMBUS is a multiobjective optimization method capable of solving nondifferentiable and nonconvex problems. We describe the NIMBUS algorithm and its implementation WWW-NIMBUS. To our knowledge WWW-NIMBUS is the first interactive multiobjective optimization system on the Internet. The main principles of its implementation are centralized computing and a distributed interface. Typically, the delivery and update of any software is problematic. Limited computer capacity may also be a problem. Via the Internet, there is only one version of the software to be updated and any client computer has the capabilities of a server computer. Further, the World-Wide Web (WWW) provides a graphical …
Helmholtz equation in unbounded domains: some convergence results for a constrained optimization problem
2016
We consider a constrained optimization problem arising from the study of the Helmholtz equation in unbounded domains. The optimization problem provides an approximation of the solution in a bounded computational domain. In this paper we prove some estimates on the rate of convergence to the exact solution.
A Bayesian Learning Automaton for Solving Two-Armed Bernoulli Bandit Problems
2008
The two-armed Bernoulli bandit (TABB) problem is a classical optimization problem where an agent sequentially pulls one of two arms attached to a gambling machine, with each pull resulting either in a reward or a penalty. The reward probabilities of each arm are unknown, and thus one must balance between exploiting existing knowledge about the arms, and obtaining new information. In the last decades, several computationally efficient algorithms for tackling this problem have emerged, with learning automata (LA) being known for their ?-optimality, and confidence interval based for logarithmically growing regret. Applications include treatment selection in clinical trials, route selection in …
Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms
2016
We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in…
Exploring Multi-Objective Optimization for Multi-Label Classifier Ensembles
2019
Multi-label classification deals with the task of predicting multiple class labels for a given sample. Several performance metrics are designed in the literature to measure the quality of any multi-label classification technique. In general existing multi-label classification approaches focus on optimizing only a single performance measure. The current work builds on the hypothesis that a weighted ensemble of multiple multi-label classifiers will lead to obtain improved results. The appropriate weight combinations for combining the outputs of multiple classifiers can be selected after simultaneously optimizing different multi-label classification metrics like micro F1, hamming loss, 0/1 los…
Optimal Bounds on Plastic Deformations for Bodies Constituted of Temperature-Dependent Elastic Hardening Material
1997
Bounds are investigated on the plastic deformations in a continuous solid body produced during the transient phase by cyclic loading not exceeding the shakedown limit. The constitutive model employs internal variables to describe temperature-dependent elastic-plastic material response with hardening. A deformation bounding theorem is proved. Bounds turn out to depend on some fictitious self-stresses and mechanical internal variables evaluated in the whole structure. An optimization problem, aimed to make the bound most stringent, is formulated. The Euler-Lagrange equations related to this last problem are deduced and they show that the relevant optimal bound has a local character, i.e., it …
A comparison of different optimization algorithms for retrieving aerosol optical depths from satellite data: an example of using a dual-angle algorit…
2011
Optimization techniques are often used in remote sensing retrieval of surface or atmospheric parameters. Nevertheless, different algorithms may exhibit different performances for the same optimization problem. Comparison of some classic optimization approaches in this article aims to select the best method for retrieving aerosol opacity, or even for other parameters, from remotely sensed data. Eight frequently used optimization algorithms were evaluated using both simulated data and actual AATSR advanced along track scanning radiometer data. Several typical land cover types and aerosol opacity levels were also considered in the simulations to make the tests more representative. It was obser…
Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels
2017
Interference is a key bottleneck in wireless communication systems. Interference alignment is a management technique that align interference from other transmitters in the least possibly dimension subspace at each receiver and provides the remaining dimensions for free interference signal. An uncoordinated interference is an example of interference which cannot be aligned coordinately with interference from coordinated part; consequently, the performance of interference alignment approaches are degraded. In this paper, we propose a rank minimization method to enhance the performance of interference alignment in the presence of uncoordinated interference sources. Firstly, to obtain higher mu…