scholarly journals Model-based optimization of ARINC-653 partition scheduling

2021 ◽  
Author(s):  
Pujie Han ◽  
Zhengjun Zhai ◽  
Brian Nielsen ◽  
Ulrik Nyman
Keyword(s):  
Evolutionary Algorithm ◽  
Timed Automata ◽  
Optimization Method ◽  
Optimization Approach ◽  
Model Checker ◽  
Genetic Operators ◽  
Temporal Isolation ◽  
Model Based ◽  
Partitioned Scheduling ◽  
Self Adaptation

AbstractThe architecture of ARINC-653 partitioned scheduling has been widely applied to avionics systems owing to its robust temporal isolation among applications. However, this partitioning mechanism causes the problem of how to optimize the partition scheduling of a complex system while guaranteeing its schedulability. In this paper, a model-based optimization approach is proposed. We formulate the problem as a parameter sweep application, which searches for the optimal partition scheduling parameters with respect to minimum processor occupancy via an evolutionary algorithm. An ARINC-653 partitioned scheduling system is modeled as a set of timed automata in the model checker UPPAAL. The optimizer tentatively assigns parameter settings to the models and subsequently invokes UPPAAL to verify schedulability as well as evaluate promising solutions. The parameter space is explored with an evolutionary algorithm that combines refined genetic operators and the self-adaptation of evolution strategies. The experimental results show the applicability of our optimization method.

The Application of the Combination of Monte Carlo Optimization Method based QSAR Modeling and Molecular Docking in Drug Design and Development

2020 ◽  
Vol 20 (14) ◽  
pp. 1389-1402 ◽  
Author(s):  
Maja Zivkovic ◽  
Marko Zlatanovic ◽  
Nevena Zlatanovic ◽  
Mladjan Golubović ◽  
Aleksandar M. Veselinović
Keyword(s):  
Monte Carlo ◽  
Molecular Docking ◽  
Computer Calculation ◽  
Molecular Graph ◽  
Optimization Method ◽  
Docking Studies ◽  
Optimization Approach ◽  
Qsar Modeling ◽  
Monte Carlo Optimization ◽  
Molecular Docking Studies

In recent years, one of the promising approaches in the QSAR modeling Monte Carlo optimization approach as conformation independent method, has emerged. Monte Carlo optimization has proven to be a valuable tool in chemoinformatics, and this review presents its application in drug discovery and design. In this review, the basic principles and important features of these methods are discussed as well as the advantages of conformation independent optimal descriptors developed from the molecular graph and the Simplified Molecular Input Line Entry System (SMILES) notation compared to commonly used descriptors in QSAR modeling. This review presents the summary of obtained results from Monte Carlo optimization-based QSAR modeling with the further addition of molecular docking studies applied for various pharmacologically important endpoints. SMILES notation based optimal descriptors, defined as molecular fragments, identified as main contributors to the increase/ decrease of biological activity, which are used further to design compounds with targeted activity based on computer calculation, are presented. In this mini-review, research papers in which molecular docking was applied as an additional method to design molecules to validate their activity further, are summarized. These papers present a very good correlation among results obtained from Monte Carlo optimization modeling and molecular docking studies.

Optimization of a Shock Absorber Design Using Model-Based Approach

2012 ◽  
Vol 452-453 ◽  
pp. 1351-1355 ◽  
Author(s):  
Grzegorz Wszołek ◽  
Piotr Czop ◽  
Dawid Jakubowski ◽  
Damian Slawik
Keyword(s):  
Automotive Industry ◽  
Shock Absorber ◽  
Flow Characteristic ◽  
Optimization Method ◽  
Design Parameters ◽  
Coupled Models ◽  
Model Based ◽  
Noise Evaluation ◽  
Optimal Values ◽  
Application Scope

The aim of this paper is to demonstrate a possibility to optimize a shock absorber design to minimize level of vibrations with the use of model-based approach. The paper introduces a proposal of an optimization method that allows to choose the optimal values of the design parameters using a shock absorber model to minimize the level of vibrations. A model-based approach is considered to obtain the optimal pressure-flow characteristic by simulations conducted with the use of coupled models, including the damper and the servo-hydraulic tester model. The presence of the tester model is required due to high non-linear coupling of the tested object (damper) and the tester itself to be used for noise evaluation. This kind of evaluation is used in the automotive industry to investigate dampers, as an alternative to vehicle-level tests. The paper provides numerical experimental case studies to show application scope of the proposed method

Distribution Network Reconfiguration Using an Approximate Optimization Approach

2013 ◽  
Vol 303-306 ◽  
pp. 1276-1279
Author(s):  
Hai Na Rong ◽  
Yan Hui Qin
Keyword(s):  
Evolutionary Algorithm ◽  
Distribution Network ◽  
Operating Conditions ◽  
Distribution Automation ◽  
Optimization Approach ◽  
Network Reconfiguration ◽  
Power Network ◽  
Distribution Network Reconfiguration ◽  
Service Restoration ◽  
Integer Programming Problems

Power network reconfiguration is an important process in the improvement of operating conditions of a power system and in planning studies, service restoration and distribution automation when remote-controlled switches are employed. This paper presents the use of a quantum-inspired evolutionary algorithm to solve the distribution network reconfiguration problem. The quantum- inspired evolutionary algorithm is the combination product of quantum computing and evolutionary computation and is suitable for a class of integer programming problems such as the distribution network reconfiguration problem. After the analysis and formulation of the distribution network reconfiguration problem, the effectiveness and feasibility of the introduced method is verified by a large number of experiments.

scholarly journals Online On-the-Fly Testing of Real-time Systems

2003 ◽  
Vol 10 (49) ◽  
Author(s):  
Marius Mikucionis ◽  
Kim G. Larsen ◽  
Brian Nielsen
Keyword(s):  
Real Time ◽  
Test Generation ◽  
Timed Automata ◽  
Online Testing ◽  
Real Time Systems ◽  
Model Checker ◽  
Test Specification ◽  
And Performance ◽  
Automata Network ◽  
Time Systems

In this paper we present a framework, an algorithm and a new tool for online testing of real-time systems based on symbolic techniques used in UPPAAL model checker. We extend UPPAAL timed automata network model to a test specification which is used to generate test primitives and to check the correctness of system responses including the timing aspects. We use timed trace inclusion as a conformance relation between system and specification to draw a test verdict. The test generation and execution algorithm is implemented as an extension to UPPAAL and experiments carried out to examine the correctness and performance of the tool. The experiment results are promising.

scholarly journals A two-stage evolutionary optimization approach for an irrigation system design

2016 ◽  
Vol 19 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Milan Cisty ◽  
Zbynek Bajtek ◽  
Lubomir Celar
Keyword(s):  
Water Distribution ◽  
Irrigation System ◽  
Optimal Solution ◽  
Water Distribution Network ◽  
Search Space ◽  
Optimization Method ◽  
Global Optimum ◽  
Optimization Approach ◽  
Nsga Ii ◽  
Irrigation Network

In this work, an optimal design of a water distribution network is proposed for large irrigation networks. The proposed approach is built upon an existing optimization method (NSGA-II), but the authors are proposing its effective application in a new two-step optimization process. The aim of the paper is to demonstrate that not only is the choice of method important for obtaining good optimization results, but also how that method is applied. The proposed methodology utilizes as its most important feature the ensemble approach, in which more optimization runs cooperate and are used together. The authors assume that the main problem in finding the optimal solution for a water distribution optimization problem is the very large size of the search space in which the optimal solution should be found. In the proposed method, a reduction of the search space is suggested, so the final solution is thus easier to find and offers greater guarantees of accuracy (closeness to the global optimum). The method has been successfully tested on a large benchmark irrigation network.

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