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Designing a sustainable recovery network for waste from electrical and electronic equipment using a genetic algorithm

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INTERNATIONAL JOURNAL OF ENVIRONMENT AND SUSTAINABLE DEVELOPMENT 2017年第1期16卷 60-79页

作者： Shokouhyar, Sajjad Aalirezaei, Armin Shahid Beheshti Univ Management & Accounting Fac Dept Informat Technol GC Tehran Iran Semnan Univ Dept Ind Engn Semnan Iran

In recent years, reverse logistic and closed-loop supply chain issues have became more important due to environmental, social and economic reasons. Product recovery which comprises recycling, remanufacturing, repairing and disposing requires an efficient reverse logistic network. Among used products, waste electrical and electronic equipment (WEEE) has become a major problem for developing countries due to its harmful effects. WEEE contains hazardous materials that may have an impact on both environment and human health if it is properly managed. On the contrary, valuable materials can be extracted if it is controlled properly. Therefore, decision makers should give consideration to design an efficient reverse logistic network to manage WEEE. In this paper, a mathematical model of two-stage RL network has been developed based on sustainable development objectives in which economic, environmental and social objectives are considered simultaneously. A multi objective genetic algorithm (MOGA) is developed to determine the best locations of collection centres and recycling plants. In result, the decision makers can make the trade-off between environmental issues and economic and social impacts. The proposed model is examined through a real case from Iran's WEEE current situation.

关键词： reverse logistic network multi objective genetic algorithm MOGA none dominated sorting genetic algorithm-II NSGA-II waste electrical and electronic equipment WEEE sustainable development

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A Comparison of Four Data Selection Methods for Artificial Neural Networks and Support Vector Machines

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IFAC-PapersOnLine 2017年第1期50卷 11227-11232页

作者： Khosravani H. Ruano A. Ferreira P.M. Faculty of Science and Technology University of Algarve IDMEC Instituto Superior Técnico Universidade de Lisboa Faro Faro Portugal LaSIGE Faculdade de Ciências Universidade de Lisboa Portugal

The performance of data-driven models such as Artificial Neural Networks and Support Vector Machines relies to a good extent on selecting proper data throughout the design phase. This paper addresses a comparison of four unsupervised data selection methods including random, convex hull based, entropy based and a hybrid data selection method. These methods were evaluated on eight benchmarks in classification and regression problems. For classification, Support Vector Machines were used, while for the regression problems, multi-Layer Perceptrons were employed. Additionally, for each problem type, a non-dominated set of Radial Basis Functions Neural Networks were designed, benefiting from a multi objective genetic algorithm. The simulation results showed that the convex hull based method and the hybrid method involving convex hull and entropy, obtain better performance than the other methods, and that MOGA designed RBFNNs always perform better than the other models. © 2017

关键词： Artificial Neural Networks Convex Hull algorithms Entropy multi objective genetic algorithm Support Vector Machines

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A Comparison of Four Data Selection Methods for Artificial Neural Networks and Support Vector Machines

A Comparison of Four Data Selection Methods for Artificial N...

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Khosravani, H. Ruano, A. Ferreira, P. M. Univ Algarve Fac Sci & Technol Faro Portugal Univ Lisbon Inst Super Tecn IDMEC Lisbon Portugal Univ Lisbon Fac Ciencias LaSIGE Lisbon Portugal

关键词： Artificial Neural Networks Convex Hull algorithms Entropy multi objective genetic algorithm Support Vector Machines

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A Novel Approach For Combinatorial Test Case Generation Using multi objective Optimization 7

A Novel Approach For Combinatorial Test Case Generation Usin...

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7th International Conference on Computer and Knowledge Engineering (ICCKE)

作者： Sabbaghi, Arash Keyvanpour, Mohammad Reza Islamic Azad Univ Qazvin Branch Dept Comp & Informat Technol Engn Qazvin Iran Alzahra Univ Dept Comp Engn Tehran Iran

ISBN: (纸本)9781538608043

Combinatorial testing is a promising technique for testing highly-configurable systems. Software systems become larger and more complex every day, and due to the time and cost limitations, it is infeasible to test everything in a software with a large configuration space, or a graphical user interface with many settings and events. Combinatorial testing generates an interaction test suite to discover faults caused by parameter interactions using a systematic sampling method. Generation of an optimal test suite in combinatorial testing despite the necessity of determining the execution order of test cases and considering constraints is a challenging process. In this paper, we consider the combinatorial testing as a multiobjective optimization problem and propose a novel approach to generate combinatorial test cases by considering all metrics simultaneously. The experimental results showed the effectiveness of the proposed approach in generating test suites with reduced size and increased priority while the higher priority test cases are generated earlier and the higher priority parameter-values appear more frequently.

关键词： software testing automatic test case generation combinatorial testing covering array pairwise testing multi objective genetic algorithm NSGA-II

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Prediction, minimization and propagation of sonic boom from supersonic bodies 55

Prediction, minimization and propagation of sonic boom from ...

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55th AIAA Aerospace Sciences Meeting

作者： Li, Junhui Krampf, Jeffrey Mitchell, James Agarwal, Ramesh K. Washington University in St. Louis Dept. of Mechanical Engineering & Materials Science St. LouisMO63130 United States

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

This paper first describes the numerical simulation and shape optimization of the Lockheed SEEB-ALR and 69 degree Delta wing-body for computing the sonic boom signature in the nearfield and its minimization using a genetic algorithm. Then the propagation of sonic boom in the atmosphere is simulated all the way to the ground for both the original and optimized body shapes. For flow field calculation, the commercial CFD flow solver ANSYS Fluent is employed. The near field pressure disturbance is used to determine the strength of the sonic boom signature. The computational results for the two cases are compared with the experimental data. The body shapes are then optimized using a single-objective genetic algorithm. The results show a significant decrease in strength of the sonic boom. The pressure data from these two models is then scaled and propagated through the atmosphere using the NASA Langley Research Center code sBOOM to predict the far field signature of these bodies at the scale of a commercial supersonic aircraft. © 2017 by The Aerospace Corporation.

关键词： Sonic Booms Delta Wing multi objective genetic algorithm Commercial Aircraft Shape Optimization NASA Langley Research Center ANSYS Computing Numerical Simulation Wind Tunnel Models

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Energetic, Economic and Environmental (3E) Optimization of Solar Assisted Heat Pump Using Low GWP Refrigerant R1234ze(E) for High Temperature Application 3

Energetic, Economic and Environmental (3E) Optimization of S...

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3rd International Conference on Power Generation Systems and Renewable Energy Technologies (PGSRET)

作者： Nasruddin, Nasruddin Alhamid, M. Idrus Aisyah, Nyayu Univ Indonesia Dept Mech Engn Depok Indonesia

ISBN: (纸本)9781509053537

A combination of solar thermal collectors and heat pumps in a solar assisted heat pump for high temperature application at 105 degrees C is modeled and optimized. The model is designed by using Matlab software. The optimization procedure, coefficient of performance and total cost becomes the objective functions while the evaporating temperature, suction compressor temperature and condensing temperature are selected as constraints. multi objective genetic algorithm is used to find the optimum value of those selected constraints. The optimization is performed by using a low GWP refrigerant, R1234ze (E). The result showed that an evaporating temperature of 319 K, suction compressor temperature of 372 K and condensing temperature of 379 K indicated the optimum condition of solar assisted heat pump with COP of 5.04 and total cost of 82,678 US$.

关键词： solar assisted heat pump COP total cost multi objective genetic algorithm

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Studies on wingtip geometries by optimum spanwise lift distribution design method 55

Studies on wingtip geometries by optimum spanwise lift distr...

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55th AIAA Aerospace Sciences Meeting

作者： Oda, Yuki Rinoie, Kenichi Yuhara, Tatsunori Department of Aeronautics and Astronautics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Next Generation Aeronautical Innovation Hub Center Japan Aerospace Exploration Agency 6-13-1 Osawa MitakaTokyo181-0015 Japan

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

Wingtip devices are used as one of the ways to reduce induced drag. This paper aims to investigate new wingtip geometries applicable for the next generation transonic aircraft. First, a design method of optimum spanwise lift distributions, which can attain the minimum induced drag, has been constructed. This design method is called the Inverse Vortex Lattice Method (Inverse VLM), and it can mathematically optimize spanwise lift distributions. The multi objective genetic algorithm (MOGA) with the Inverse VLM is conducted to search wingtip configurations, which takes aerodynamics and structural weight into consideration. A downward or upward pointing rakelet, which is a wingtip configuration with a raked wingtip accompanied by a downward or upward pointing winglet section, is mainly considered. Beneficial reduction of induced drag is indicated for the downward pointing rakelet. Second, the detailed performances in the transonic region of the wingtip configurations obtained by MOGA are analyzed by CFD. Structural weight estimations are also conducted. The upward and downward pointing rakelets with a 105% span length achieve a drag reduction more than 10 counts compared with the baseline. The downward pointing rakelet indicates the largest decrease in total weight. Additionally, primary wingtip geometries, such as winglets and rakelets, are analyzed by CFD and the differences among them are discussed. © 2017 by Yuki Oda, Kenichi Rinoie and Tatsunori Yuhara.

关键词： Freestream Velocity Fuselages Structural Element Wingtip Device multi objective genetic algorithm Quasi Vortex Lattice Method Transonic Aircraft Wingtip Vortices Camber Influence Coefficients

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Airfoil optimisation for DBD plasma actuator in a wind energy environment: Design and experimental study 55

Airfoil optimisation for DBD plasma actuator in a wind energ...

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55th AIAA Aerospace Sciences Meeting

作者： Carbonell Batlle, E. Pereira, R. Kotsonis, M. de Oliveira, G. Terrassa School of Industrial Aerospace and Audiovisual Engineering Polytechnic University of Catalonia Colom 11 Terrassa08222 Spain Faculty of Aerospace Engineering Delft University of Technology Kluyverweg 1 Delft2629 HS Netherlands

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

This article describes and experimentally evaluates an airfoil design methodology, in which airfoils are designed to be simultaneously suited for wind energy applications and to employ Dielectric Barrier Discharge Plasma Actuators (DBD PA) as active flow control (AFC) devices. The design process is carried out using a multi-objective optimizer solved with a genetic algorithm, which evaluates 150 airfoil candidates along 30 generations to optimize their performance. The airfoil candidate evaluation is done with two cost functions: the wind energy suitability cost function compares the non-actuated airfoil performance with a reference group of airfoils, while the AFC suitability cost function assesses the changes in the CL(named CLauthority) caused by the DBD PA actuation. From the generated airfoils, a candidate is selected and tested experimentally at design and off-design conditions. The parametric study on the experimental airfoil performance includes different wind speeds, DBD voltage amplitude and actuation direction. From multiple off-design condition tests it is possible to observe a maximum actuation efficiency at design condition, since higher voltages applied do not lead to a significant increase of the CLauthority and different wind speeds and actuation direction reduce the actuation efficiency. Additionally, the experimental angle of attack range at which DBD actuation induces lift variations compares well with simulated data, and the predicted trends of the actuator impact are confirmed, even though the experimental dCl is smaller than simulated results. The present article demonstrates the potential of the studied airfoil design process to create the future generation of plasma actuated wind energy airfoils. © 2017 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Wind Energy Plasma Actuator Airfoil Dielectric Barrier Discharge Aerodynamic Performance Active Flow Control multi objective genetic algorithm Wind Turbine Laminar Turbulent Transition Wind Tunnel Tests

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Computation of rarefaction effects on a blunt body in hypersonic flow 55

Computation of rarefaction effects on a blunt body in hypers...

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55th AIAA Aerospace Sciences Meeting

作者： Huang, Guanzheng Agarwal, Ramesh K. Department of Mechanical Engineering and Materials Science Washington University in St. Louis St. LouisMO63130 United States

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

High-speed vehicles such as next generation launch vehicles or reusable spacecraft experience different flow regimes during flight due to change in atmospheric density. At high altitude, due to low density the flow becomes rarefied and the rarefaction effects cannot be accurately modeled by the Navier-Stokes equations with no-slip boundary conditions. In low density flow, for predicting the small rarefaction effects, Maxwell suggested the use of slip boundary conditions with Navier-Stokes equations. In this paper, a UDF (User Defined Function) which employs the velocity slip and temperature jump boundary conditions at the wall is applied to the commercial flow solver ANSYS FLUENT with the compressible Reynolds Averaged Navier-Stokes (RANS) equations in conjunction with the Shear-Stress-Transport (SST) k-ω turbulence model to simulate the flow around a blunt body in hypersonic flow. The results of both no-slip condition and slip boundary conditions for flow past an axisymmetric body with Knudsen number Kn = 0.0003354, 0.00838, 0.0167, 0.0418, and 0.1are computed and the effect of rarefaction on heat transfer and drag is analyzed and discussed. In addition, a multi-objective genetic algorithm is used to optimize the shape of the blunt body for minimizing both the drag and heat flux. A Pareto optimal front is obtained for different optimization weights of drag vs. heat transfer for Kn = 0.0167. © 2017 by Guanzheng Huang and Ramesh K. Agarwal.

关键词： Hypersonic Flows Freestream Mach Number Reynolds Averaged Navier Stokes Heat Transfer multi objective genetic algorithm Computational Fluid Dynamics Heat Flux Navier Stokes Equations Reusable Spacecraft Atmospheric Density

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Application of numerical optimisation to support engineering design 58

Application of numerical optimisation to support engineering...

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58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017

作者： Keskin, Akin Engineering Capability Rolls-Royce plc PO Box 31 DerbyDE24 8BJ United Kingdom

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