Feature selection using multi-objective evolutionary algorithms : application to cardiac SPECT diagnosis

An optimization methodology based on the use of Multi-Objective Evolutionary Algorithms (MOEA) in order to deal with problems of feature selection in data mining was proposed. For that purpose a Support Vector Machines (SVM) classifier was adopted. The aim being to select the best features and optimize the classifier parameters simultaneously while minimizing the number of features necessary and maximize the accuracy of the classifier and/or minimize the errors obtained. The validity of the methodology proposed was tested in a problem of cardiac Single Proton Emission Computed Tomography (SPECT). The results obtained allow one to conclude that MOEA is an efficient feature selection approach and the best results were obtained when the accuracy, the errors and the classifiers parameters are optimized simultaneously

Melting of immiscible physical and compatibilized polymer blends in single screw extruders

Melting is a major step in plasticating single screw extrusion, but most of the existing phenomenological know how was gathered by performing Maddock-type experiments with homopolymers. Given the current widespread industrial use of polymer blends, it is worth determining whether the same mechanisms and mathematical models apply, or whether different sequences develop. This work reports the results of Maddock-type experiments using a PA6/PP blend, both in its immiscible and compatibilized varieties. A melting mechanism combining the features of the classical Tadmor mechanism and of the dispersed melting mechanism, also previously reported in the literature, was observed

Morphology development of immiscible polymer blends during melting in single-screw extruders : effect of composition and compatibilization

Melting in single screw extruders began to be studied in the fifties, based on the pioneering work of Maddock. Most theoretical and experimental studies used homopolymers as model systems. However, in practice, there has been a considerable evolution in terms of the complexity of the materials being extruded. In the case of polymer blends, the morphology developed during melting should determine the final blend properties. Therefore, this work aims at investigating the morphology evolution during the melting stage of immiscible physical and chemically compatibilized PA6/PP blends. In general, the sequence of steps of morphology evolution reported for twin screw extruders and batch mixers was observed, though adapted to the flow kinematics along a helical single screw channel. The global morphological development is not affected by blend composition, but distinct domains seem to be formed when in situ reactive compatibilization takes place

Melting of polymer blends and concomitant morphology development in single screw extruders

The current understanding of the melting stage in single screw extruders results from pioneering research efforts that were initiated in the fifties and continued for more than thirty years. Most of these theoretical and experimental studies used homopolymers as model systems, whereas in industrial practice there has been a considerable evolution in terms of the complexity of the materials being extruded. This work reports an attempt to monitor the melting sequence and the morphology development of immiscible physical and chemically compatibilized PA6/PP blends. A hybrid melting mechanism, incorporating elements of the Tadmor and of the Dispersive melting mechanisms seems to develop; the early stages of morphology development seem to be similar to those observed in the Haake mixer and Twin-screw extruder

Weighted stress function method for multiobjective evolutionary algorithm based on decomposition

Multiobjective evolutionary algorithm based on decomposition (MOEA/D) is a well established state-of-the-art framework. Major concerns that must be addressed when applying MOEA/D are the choice of an appropriate scalarizing function and setting the values of main control parameters. This study suggests a weighted stress function method (WSFM) for fitness assignment in MOEA/D. WSFM establishes analogy between the stress-strain behavior of thermoplastic vulcanizates and scalarization of a multiobjective optimization problem. The experimental results suggest that the proposed approach is able to provide a faster convergence and a better performance of final approximation sets with respect to quality indicators when compared with traditional methods. The validity of the proposed approach is also demonstrated on engineering problems.This work has been supported by FCT - Fundação para a Ciência e Tecnologia in the scope of the project: PEst-OE/EEI/UI0319/2014.info:eu-repo/semantics/publishedVersio

A scaling-up methodology for co-rotating twin-screw extruders

Scaling-up of co-rotating twin screw extruders is studied as a multi-objective optimization problem where the aim is to define the geometry/operating conditions of the target extruder that minimize the differences between the values of the performance criteria that depict the reference and target extruders. Three computational experiments are discussed. These preliminary results seem encouraging

Use of multi-objective evolutionary algorithms in extrusion scale-up

Extrusion scale-up consists in ensuring identical thermo-mechanical environments in machines of different dimensions, but processing the same material. Given a reference extruder with a certain geometry and operating point, the aim is to define the geometry and operating conditions of a target extruder (of a different magnitude), in order to subject the material being processed to the same flow and heat transfer conditions, thus yielding products with the same characteristics. Scale-up is widely used in industry and academia, for example to extrapolate the results obtained from studies performed in laboratorial machines to the production plant. Since existing scale-up rules are very crude, as they consider a single performance measure and produce unsatisfactory results, this work approaches scale-up as a multi-criteria optimization problem, which seeks to define the geometry/operating conditions of the target extruder that minimize the differences between the values of the criteria for the reference and target extruders. Some case studies are discussed in order to validate the concept

The use of evolutionary algorithms to solve practical problems in polymer extrusion

This work aims at selecting the operating conditions and designing screws that optimize the performance of single-screw and co-rotating twin-screw extruders, which are machines widely used by the polymer processing industry. A special MOEA, denoted as Reduced Pareto Set Genetic Algorithm, RPSGAe, is presented and used to solve these multiobjective combinatorial problems. Twin screw design is formulated as a Travelling Salesman Problem, TSP, given its discrete nature. Various case studies are analyzed and their validity is discussed, thus demonstrating the potential practical usefulness of this approach

Technological and design aspects of the processing of composites and nanocomposites. Volume III

Processing of composites and nanocomposites materials constitutes nowadays an important area of research given the growing interest by these types of materials due to its singular properties, namely in what concerns technological and design aspects. This monography presents the developments taking place in the framework of the NEWEX project during the fourth year of its duration, which is a sequence of other two previous monographies. The main objective of the NEWEX project entitled “Investigation and development of a new generation of machines for the processing of composite and nanocomposites materials” is the exchange of researchers from the institutions participating in the project. Another important objective consists in develop permanent international and inter-sector collaboration between academic research centres (Lublin University of Technology, Technical University of Kosice, University of Minho) and industrial organizations (Zamak-Mercator LLC and SEZ-Krompachy a.s., Dirmeta UAB). The contents of this book reflects the work done within the NEWEX project. It starts by presenting the results obtained concerning new concepts for the extruder parts studied and the manufacturing of those extruder parts. Then, some approaches for modelling and optimizing and to study experimentally the process are described, which includes mixing analysis and monitoring. Finally, a practical and state-of-theart application of the extrusion is identified, namely 3D printing. It is expected that the nine chapters of this monography be useful to the industry of plastics processing and for scientific organisations dealing with technologies and processing of polymer composites and nanocomposites

RPSGAe - Reduced Pareto Set Genetic Algorithm : application to polymer extrusion

Publicado na serie "Lecture notes in economics and mathematical systems" ; 535In this paper a Multiobjective Optimization Genetic Algorithm, denoted as Reduced Pareto Set Genetic Algorithm with Elitism (RPSGAe), is presented and its performance is assessed. The algorithm is compared with other Evolutionary Multi-Objective Algorithms - EMOAs (SPEA2, PAES and NSGA-II) using problems from the literature and statistical comparison techniques. The results obtained showed that the RPSGAe algorithm has good overall performance. Finally, the RPSGAe algorithm was applied to the optimization of the polymer extrusion process. The aim is to implement an automatic optimization scheme capable of defining the values of important process parameters, such as operating conditions and screw geometry, yielding the best performance in terms of prescribed attributes. The results obtained for specific case studies have physical meaning and correspond to a successful process optimization