This work experimentally investigates model-based approaches for optimizing the performance of parameterized randomized algorithms. Such approaches build a response surface model and use this model for finding good parameter settings of the given algorithm. We evaluated two methods from the literature that are based on Gaussian process models: sequential parameter optimization (SPO) (Bartz-Beie...

operating parameters and membrane characteristics strongly affect the performance of electrodialysis reversal systems. the most impactful factors are applied voltage, flow rate, temperature, initial feed composition, and ion exchange membrane characteristics; the ph of the feed also has an effect, although to a lesser extent. to determine more precisely how all of these factors impact performan...

1. Abstract Nowadays, process optimization plays an important role in the chemical industries, providing many benefits. The aim of this work is to present a new framework for process optimization of chemical industries based on rigorous process models and with many integrated features, such as: customized thermodynamic data package, dynamic and steady-state simulation, optimization, parameter e...

This paper considers a parametric nonlinear least square (NLS) optimization problem. Unlike a classical NLS problem statement, we assume that a nonlinear optimized system depends on two arguments: an input vector and a parameter vector. The input vector can be modified to optimize the system, while the parameter vector changes from one optimization iteration to another and is not controlled. Th...

The final quality and cost of a manufactured product are determined to a large extent by the engineering design of the product and its production process through activities of off-line quality control methods, namely, System Design, Parameter Design and Tolerance Design. However, in the context of most non-industrialized countries, the off-line quality activities of product design and system de...

This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time...

This paper presents a methodology, based on the taguchi parameter design approach, for the optimization of process parameters for bismuth recovery from aqueous solutions. The process parameters considered are [Bi3+], [NaCl], temperature, and cathodic current density. In addition, cell voltage and current efficiency as two responses have been considered. An orthogonal array L9, the signal-to-noi...

Surface roughness, an indicator of surface quality is one of the most specified customer requirements in a machining process. For efficient use of machine tools, optimum cutting parameters (speed, feed and depth of cut) are required. Therefore it is necessary to find a suitable optimization method which can find optimum values of cutting parameters for minimizing surface roughness. The turning ...

The process of identifying the optimal parameters for an optimization algorithm or a machine learning one is usually costly, involves the search of a large, possibly infinite, space of candidate parameter sets, and may not guarantee optimality. Various attempts have been made to automate this process. Our work attempts to explore this research area further by analyzing the behavior of a simple ...

The process of identifying the optimal parameters for an optimization algorithm or a machine learning one is usually costly, involves the search of a large, possibly infinite, space of candidate parameter sets, and may not guarantee optimality. Various attempts have been made to automate this process. Our work attempts to explore this research area further by analyzing the behavior of a simple ...