Optimizing Data Measurements at Test Beds Using Multi-Step Genetic Algorithms
نویسنده
چکیده
Series of measurements should be planned carefully in order to reduce the costs and to allow an efficient execution at measuring devices. For this planning process, we present a multi-step optimization method using genetic algorithms. As a concrete application, we arrange a set of Design of Experiment measuring points appearing during the calibration of combustion engines in an optimal way. Key-Words: Genetic Algorithm, Traveling Salesman Problem, Multi-Step Optimization, Adjacency Coding, Variable Alphabet Coding, Monte Carlo Algorithm, Design of Experiments.
منابع مشابه
Pareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...
متن کاملModeling and Multi-Objective Optimization of Stall Control on NACA0015 Airfoil with a Synthetic Jet using GMDH Type Neural Networks and Genetic Algorithms
This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. Thenumerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 106 a...
متن کاملUsing and comparing metaheuristic algorithms for optimizing bidding strategy viewpoint of profit maximization of generators
With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...
متن کاملOptimization of sediment rating curve coefficients using evolutionary algorithms and unsupervised artificial neural network
Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...
متن کاملMulti-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...
متن کامل