In orientation to new developments in evolutionary biology we propose an extension of evolutionary algorithms in two dimensions, the regulatory algorithm (RGA). It consists of two levels of vectors, the regulatory vec...
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In orientation to new developments in evolutionary biology we propose an extension of evolutionary algorithms in two dimensions, the regulatory algorithm (RGA). It consists of two levels of vectors, the regulatory vector and the structural vector. Each element of the regulatory vector is connected with one or several elements of the structural vector, but not vice versa. The connections can be interpreted as steering connections, the switching on or off of the structural elements and/or as switching orders for the structural elements. An RGA that operates with the usual genetic operators of mutation and crossover can be used for avoiding rules like penalty or default operators, it is in certain problems significantly faster than a standard genetic algorithm, and it is very suited when modeling and optimizing systems that consist themselves of different levels. Examples of RGA usage are shown, namely, the optimal dividing of socially deviant youths in a hostel, the optimal introduction of communication standards in information systems, and the allocation of employees to superiors by taking into regard the different personality types.
Feature selection is one of the important challenges in variability-intensive systems. The FCORE model is used for the description of the functional and non-functional requirements of a system from a systems engineeri...
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ISBN:
(纸本)9781509046010
Feature selection is one of the important challenges in variability-intensive systems. The FCORE model is used for the description of the functional and non-functional requirements of a system from a systems engineering point of view. In addition we demonstrate a solution for feature selection using a regulator algorithm (RGA). The RGA is a two dimensional evolutionary algorithm, with regulator genes controlling the structural genes. This allows a direct transfer of the FCORE model into the RGA, which optimizes the feature selection without constraint violations.
We describe a new evolutionary algorithm, namely the regulatory algorithm (RGA), a two dimensional extension of standard evolutionary algorithms. Its possibilities are shown by an application to the problem of optimiz...
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ISBN:
(纸本)9781509006229
We describe a new evolutionary algorithm, namely the regulatory algorithm (RGA), a two dimensional extension of standard evolutionary algorithms. Its possibilities are shown by an application to the problem of optimizing room allocation plans with real data from the University Duisburg-Essen (Germany). The results of the RGA application match in most cases the factual room allocations of the university and are in several cases better, i.e. the RGA results fulfill more necessary conditions.
We describe the regulatory algorithm (RGA), a two dimensional extension of standard evolutionary algorithms. Its possibilities are shown by an application to the problem of optimizing timetabling for exams with real d...
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ISBN:
(纸本)9781509042401
We describe the regulatory algorithm (RGA), a two dimensional extension of standard evolutionary algorithms. Its possibilities are shown by an application to the problem of optimizing timetabling for exams with real data from the University Duisburg-Essen (Germany). The results of the RGA application show that the room allocation problem for written exams can be satisfactory solved in a few minutes. In addition we compared the RGA with a standard GA. The RGA was significantly better in all experiments;in particular the GA could not fulfill all distribution demands in contrast to the RGA.
We describe the regulatory algorithm (RGA), a two dimensional extension of standard evolutionary algorithms. Its possibilities are shown by an application to the problem of optimizing timetabling for exams with real d...
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ISBN:
(纸本)9781509042418
We describe the regulatory algorithm (RGA), a two dimensional extension of standard evolutionary algorithms. Its possibilities are shown by an application to the problem of optimizing timetabling for exams with real data from the University Duisburg-Essen (Germany). The results of the RGA application show that the room allocation problem for written exams can be satisfactory solved in a few minutes. In addition we compared the RGA with a standard GA. The RGA was significantly better in all experiments;in particular the GA could not fulfill all distribution demands in contrast to the RGA.
Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to ...
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Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to osteoarthritis (OA). Despite extensive in vitro and in vivo research, it remains unclear how the changes in cartilage composition and structure that occur during cartilage degeneration after injury, interact. Recently, in silico techniques provide a unique integrated platform to investigate the causal mechanisms by which the local mechanical environment of injured cartilage drives cartilage degeneration. Here, we introduce a novel integrated Cartilage Adaptive REorientation Degeneration (CARED) algorithm to predict the interaction between degenerative variations in main cartilage constituents, namely collagen fibril disorganization and degradation, proteoglycan (PG) loss, and change in water content. The algorithm iteratively interacts with a finite element (FE) model of a cartilage explant, with and without variable depth to full-thickness defects. In these FE models, intact and injured explants were subjected to normal (2 MPa unconfined compression in 0.1 s) and injurious mechanical loading (4 MPa unconfined compression in 0.1 s). Depending on the mechanical response of the FE model, the collagen fibril orientation and density, PG and water content were iteratively updated. In the CARED model, fixed charge density (FCD) loss and increased water content were related to decrease in PG content. Our model predictions were consistent with earlier experimental studies. In the intact explant model, minimal degenerative changes were observed under normal loading, while the injurious loading caused a reorientation of collagen fibrils toward the direction perpendicular to the surface, intense collagen degradation at the surface, and intense PG loss in the superficial and middle zones. In the injured explant models, normal loading induced intense collagen degrad
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