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We have developed a new derivative-free algorithm based on Radial Basis Functions (RBFs). Derivative-free optimization is an active field of research and several algorithms have been proposed recently. Problems of this nature in the industrial setting are ...
Optimization problems due to noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the u ...
International sea-freight container transport has grown dramatically over the last years and container terminals play nowadays a key-role in the global shipping network. Increasing competition and competitiveness among terminals require more and more effic ...
International sea-freight container transport has grown dramatically over the last years and container terminals play nowadays a key-role in the global shipping network. Increasing competition and competitiveness among terminals require more and more effic ...
Starting from the basic image reconstruction problem in discrete tomography some graph theoretical models are proposed. This suggests the study of some variations and extensions of the basic problem. Applications in scheduling and timetabling are described ...
In most applications related to transportation, it is of major importance to be able to identify the global optimum of the associated optimization problem. The work we present in this paper is motivated by the optimization problems arising in the maximum l ...
We consider an optimization problem arising in the design of controllers for OLED displays. Our objective is to minimize amplitude of the electrical current through the diodes which has a direct impact on the lifetime of such a display. Modeling the proble ...
We present in this paper a new complete method for distributed constraint optimization. This is a utility-propagation method, inspired by the sum-product algorithm (Kschischang et al 2001). The original algorithm requires fixed message sizes, linear memory ...
We define the distributed, real-time combinatorial optimization problem. We propose a general, semantically well-defined notion of solution stability in such systems, based on the cost of change from an already implemented solution to the new one. This app ...
Optimization arises naturally when process performance needs improvement. This is often the case in industry because of competition – the product has to be proposed at the lowest possible cost. From the point of view of control, optimization consists in de ...
