Search results for: design optimization

Authors: B. Medjahed, M. A. Didi, B. Guezzen

Abstract:

This work concerns with the experimental study of the adsorption of the Ni(II) on bentonite. The effects of various parameters such as contact time, stirring rate, initial concentration of Ni(II), masse of clay, initial pH of aqueous solution and temperature on the adsorption yield, were carried out. The study of the effect of the ionic strength on the yield of adsorption was examined by the identification and the quantification of the present chemical species in the aqueous phase containing the metallic ion Ni(II). The adsorbed species were investigated by a calculation program using CHEAQS V. L20.1 in order to determine the relation between the percentages of the adsorbed species and the adsorption yield. The optimization process was carried out using 2³ factorial designs. The individual and combined effects of three process parameters, i.e. initial Ni(II) concentration in aqueous solution (2.10⁻³ and 5.10⁻³ mol/L), initial pH of the solution (2 and 6.5), and mass of bentonite (0.03 and 0.3 g) on Ni(II) adsorption, were studied.

Keywords: Adsorption, bentonite, factorial design, Nickel(II).

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Authors: Songtao Chang, Yongji Wang, Lei Liu, Dangjun Zhao

Abstract:

Reentry trajectory optimization is a multi-constraints optimal control problem which is hard to solve. To tackle it, we proposed a new algorithm named CDEN(Constrained Differential Evolution Newton-Raphson Algorithm) based on Differential Evolution( DE) and Newton-Raphson.We transform the infinite dimensional optimal control problem to parameter optimization which is finite dimensional by discretize control parameter. In order to simplify the problem, we figure out the control parameter-s scope by process constraints. To handle constraints, we proposed a parameterless constraints handle process. Through comprehensive analyze the problem, we use a new algorithm integrated by DE and Newton-Raphson to solve it. It is validated by a reentry vehicle X-33, simulation results indicated that the algorithm is effective and robust.

Keywords: reentry vehicle, trajectory optimization, constraint optimal, differential evolution.

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Authors: Abbas Al-Refaie, Nour Bata

Abstract:

A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.

Keywords: Market segmentation, conjoint analysis, market strategies, optimization.

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Authors: Darwin Gouwanda, S. G. Ponnambalam

Abstract:

Set covering problem is a classical problem in computer science and complexity theory. It has many applications, such as airline crew scheduling problem, facilities location problem, vehicle routing, assignment problem, etc. In this paper, three different techniques are applied to solve set covering problem. Firstly, a mathematical model of set covering problem is introduced and solved by using optimization solver, LINGO. Secondly, the Genetic Algorithm Toolbox available in MATLAB is used to solve set covering problem. And lastly, an ant colony optimization method is programmed in MATLAB programming language. Results obtained from these methods are presented in tables. In order to assess the performance of the techniques used in this project, the benchmark problems available in open literature are used.

Keywords: Set covering problem, genetic algorithm, ant colony optimization, LINGO.

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Authors: M. Bassoui, M. Ferfra, M. Chraygane, M. Ould Ahmedou, N. Elghazal, A. Belhaiba

Abstract:

Currently, the High voltage power supply for microwave generators with one magnetron uses a single-phase transformer with magnetic shunt. To contribute in the development of technological innovation in industry of manufacturing of power supplies of magnetrons for microwaves, ovens for domestic or industrial use, this original work treats the optimization of a new three-phase high voltage power supply for industrial microwaves generators with N magnetrons by phase (Treated case N=1), from its modeling with Matlab-Simulink. The design of this power supply uses three π quadruple models equivalents of new three-phase transformer with magnetic shunt of each phase. Every one supplies at its output a voltage doubler cell composed of a capacitor and a diode that in its output supplies only one magnetron.  In this work we will define a strategy that aims to reduce the volume of the transformer and the weight and cost of the entire system of the high voltage power supply, while respecting the conditions recommended by the manufacturer, concerning the current flowing in each magnetron: (Imax <1.2 A, IAv ≈ 300 mA).

 

Keywords: Optimization, Three-phase transformer, Modeling, power supply, magnetrons, Matlab Simulink, High Voltage

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Authors: Mat Syai'in, Adi Soeprijanto

Abstract:

An Optimal Power Flow based on Improved Particle Swarm Optimization (OPF-IPSO) with Generator Capability Curve Constraint is used by NN-OPF as a reference to get pattern of generator scheduling. There are three stages in Designing NN-OPF. The first stage is design of OPF-IPSO with generator capability curve constraint. The second stage is clustering load to specific range and calculating its index. The third stage is training NN-OPF using constructive back propagation method. In training process total load and load index used as input, and pattern of generator scheduling used as output. Data used in this paper is power system of Java-Bali. Software used in this simulation is MATLAB.

Keywords: Optimal Power Flow, Generator Capability Curve, Improved Particle Swarm Optimization, Neural Network

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Authors: Hansoo Kim, Seunghak Shin

Abstract:

The differential column shortening in tall buildings can be reduced by improving material and structural characteristics of the structural systems. This paper proposes structural methods to reduce differential column shortening in reinforced concrete tall buildings; connecting columns with rigidly jointed horizontal members, using outriggers, and placing additional reinforcement at the columns. The rigidly connected horizontal members including outriggers reduce the differential shortening between adjacent vertical members. The axial stiffness of columns with greater shortening can be effectively increased by placing additional reinforcement at the columns, thus the differential column shortening can be reduced in the design stage. The optimum distribution of additional reinforcement can be determined by applying a gradient based optimization technique.

Keywords: Column shortening, long-term behavior, optimization, tall building.

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Authors: Navid Mehdizadeh Afroozi, Khodakhast Isapour, Mojtaba Hakimzadeh, Abdolmohammad Davodi

Abstract:

The objective of the Economic Dispatch(ED) Problems of electric power generation is to schedule the committed generating units outputs so as to meet the required load demand at minimum operating cost while satisfying all units and system equality and inequality constraints. This paper presents a new method of ED problems utilizing the Max-Min Ant System Optimization. Historically, traditional optimizations techniques have been used, such as linear and non-linear programming, but within the past decade the focus has shifted on the utilization of Evolutionary Algorithms, as an example Genetic Algorithms, Simulated Annealing and recently Ant Colony Optimization (ACO). In this paper we introduce the Max-Min Ant System based version of the Ant System. This algorithm encourages local searching around the best solution found in each iteration. To show its efficiency and effectiveness, the proposed Max-Min Ant System is applied to sample ED problems composed of 4 generators. Comparison to conventional genetic algorithms is presented.

Keywords: Economic Dispatch (ED), Ant Colony Optimization, Fuel Cost, Algorithm.

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Authors: Pankaj Chandna, Dinesh Kumar

Abstract:

The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 Steel, Orthogonal Array, Optimization, Surface Roughness, Taguchi Methodology.

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Authors: Banaz Omer Rasheed, Parexan M. Aljaff

Abstract:

In this paper, a wide band gain–flattened discrete Raman amplifiers utilizing four optimum pump wavelengths is demonstrated.

Keywords: Fiber Raman Amplifiers, Optimization, WaveLength Division Multiplexing.

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Authors: B. Guezzen, M. A. Didi, B. Medjahed

Abstract:

An organoclay (HDTMA-B) was prepared from sodium bentonite (Na-B). The starting material was modified using the hexadecyltrimethylammonium ion (HDTMA⁺) in the amounts corresponding to 100 % of the CEC value. Batch experiments were carried out in order to model and optimize the sorption of Congo red dye from aqueous solution. The pseudo-first order and pseudo-second order kinetic models have been developed to predict the rate constant and the sorption capacity at equilibrium with the effect of temperature, the solid/solution ratio and the initial dye concentration. The equilibrium time was reached within 60 min. At room temperature (20 °C), optimum dye sorption of 49.4 mg/g (98.9%) was achieved at pH 6.6, sorbent dosage of 1g/L and initial dye concentration of 50 mg/L, using surfactant modified bentonite. The optimization of adsorption parameters mentioned above on dye removal was carried out using Box-Behnken design. The sorption parameters were analyzed statistically by means of variance analysis by using the Statgraphics Centurion XVI software.

Keywords: Adsorption, dye, factorial design, kinetic, organo-bentonite.

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

Abstract:

Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.

Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.

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Authors: Zongyan Li, Matt Best

Abstract:

This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.

Keywords: Correlation analysis, F-ratio, Levenberg-Marquardt, MSE, NARX, neural network, optimisation.

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Authors: Santanu Santra, Utpal Roy

Abstract:

Quantum-dot Cellular Automata (QCA) is one of the most substitute emerging nanotechnologies for electronic circuits, because of lower power consumption, higher speed and smaller size in comparison with CMOS technology. The basic devices, a Quantum-dot cell can be used to implement logic gates and wires. As it is the fundamental building block on nanotechnology circuits. By applying XOR gate the hardware requirements for a QCA circuit can be decrease and circuits can be simpler in terms of level, delay and cell count. This article present a modest approach for implementing novel optimized XOR gate, which can be applied to design many variants of complex QCA circuits. Proposed XOR gate is simple in structure and powerful in terms of implementing any digital circuits. In order to verify the functionality of the proposed design some complex implementation of parity generator and parity checker circuits are proposed and simulating by QCA Designer tool and compare with some most recent design. Simulation results and physical relations confirm its usefulness in implementing every digital circuit.

Keywords: Clock, CMOS technology, Logic gates, QCA Designer, Quantum-dot Cellular Automata (QCA).

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Authors: James Kuria, John Kihiu

Abstract:

This work presents a numerical model developed to simulate the dynamics and vibrations of a multistage tractor gearbox. The effect of time varying mesh stiffness, time varying frictional torque on the gear teeth, lateral and torsional flexibility of the shafts and flexibility of the bearings were included in the model. The model was developed by using the Lagrangian method, and it was applied to study the effect of three design variables on the vibration and stress levels on the gears. The first design variable, module, had little effect on the vibration levels but a higher module resulted to higher bending stress levels. The second design variable, pressure angle, had little effect on the vibration levels, but had a strong effect on the stress levels on the pinion of a high reduction ratio gear pair. A pressure angle of 25o resulted to lower stress levels for a pinion with 14 teeth than a pressure angle of 20o. The third design variable, contact ratio, had a very strong effect on both the vibration levels and bending stress levels. Increasing the contact ratio to 2.0 reduced both the vibration levels and bending stress levels significantly. For the gear train design used in this study, a module of 2.5 and contact ratio of 2.0 for the various meshes was found to yield the best combination of low vibration levels and low bending stresses. The model can therefore be used as a tool for obtaining the optimum gear design parameters for a given multistage spur gear train.

Keywords: bending stress levels, frictional torque, gear designparameters, mesh stiffness, multistage gear train, vibration levels.

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Authors: Faizan Ahmad, Lau Kok Keong, Azmi Mohd. Shariff

Abstract:

The upgrading of low quality crude natural gas (NG) is attracting interest due to high demand of pipeline-grade gas in recent years. Membrane processes are commercially proven technology for the removal of impurities like carbon dioxide from NG. In this work, cross flow mathematical model has been suggested to be incorporated with ASPEN HYSYS as a user defined unit operation in order to design the membrane system for CO2/CH4 separation. The effect of operating conditions (such as feed composition and pressure) and membrane selectivity on the design parameters (methane recovery and total membrane area required for the separation) has been studied for different design configurations. These configurations include single stage (with and without recycle) and double stage membrane systems (with and without permeate or retentate recycle). It is shown that methane recovery can be improved by recycling permeate or retentate stream as well as by using double stage membrane systems. The ASPEN HYSYS user defined unit operation proposed in the study has potential to be applied for complex membrane system design and optimization.

Keywords: CO2/CH4 Separation, Membrane Process, Membrane modeling, Natural Gas Processing

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Authors: B. Mukanova, N. Glazyrina, S. Glazyrin

Abstract:

The formulated problem of optimization of the technological process of water treatment for thermal power plants is considered in this article. The problem is of multiparametric nature. To optimize the process, namely, reduce the amount of waste water, a new technology was developed to reuse such water. A mathematical model of the technology of wastewater reuse was developed. Optimization parameters were determined. The model consists of a material balance equation, an equation describing the kinetics of ion exchange for the non-equilibrium case and an equation for the ion exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion exchange. A direct problem of calculating the impurity concentration at the outlet of the water treatment plant was numerically solved. The direct problem was approximated by an implicit point-to-point computation difference scheme. The inverse problem was formulated as relates to determination of the parameters of the mathematical model of the water treatment plant operating in non-equilibrium conditions. The formulated inverse problem was solved. Following the results of calculation the time of start of the filter regeneration process was determined, as well as the period of regeneration process and the amount of regeneration and wash water. Multi-parameter optimization of water treatment process for thermal power plants allowed decreasing the amount of wastewater by 15%.

Keywords: Direct problem, multiparametric optimization, optimization parameters, water treatment.

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Authors: George N. Prodromidis, Frank A. Coutelieris

Abstract:

Biogas can be currently considered as an alternative option for electricity production, mainly due to its high energy content (hydrocarbon-rich source), its renewable status and its relatively low utilization cost. Solid Oxide Fuel Cell (SOFC) stacks convert fuel’s chemical energy to electricity with high efficiencies and reveal significant advantages on fuel flexibility combined with lower emissions rate, especially when utilize biogas. Electricity production by biogas constitutes a composite problem which incorporates an extensive parametric analysis on numerous dynamic variables. The main scope of the presented study is to propose a detailed thermodynamic model on the optimization of SOFC-based power plants’ operation based on fundamental thermodynamics, energy and exergy balances. This model named THERMAS (THERmodynamic MAthematical Simulation model) incorporates each individual process, during electricity production, mathematically simulated for different case studies that represent real life operational conditions. Also, THERMAS offers the opportunity to choose a great variety of different values for each operational parameter individually, thus allowing for studies within unexplored and experimentally impossible operational ranges. Finally, THERMAS innovatively incorporates a specific criterion concluded by the extensive energy analysis to identify the most optimal scenario per simulated system in exergy terms. Therefore, several dynamical parameters as well as several biogas mixture compositions have been taken into account, to cover all the possible incidents. Towards the optimization process in terms of an innovative OPF (OPtimization Factor), presented here, this research study reveals that systems supplied by low methane fuels can be comparable to these supplied by pure methane. To conclude, such an innovative simulation model indicates a perspective on the optimal design of a SOFC stack based system, in the direction of the commercialization of systems utilizing biogas.

Keywords: Biogas, Exergy, Optimization, SOFC.

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Authors: Niloofar Khedri, Masoud Rahgozar, MahmoudReza Hashemi

Abstract:

Design patterns describe good solutions to common and reoccurring problems in program design. Applying design patterns in software design and implementation have significant effects on software quality metrics such as flexibility, usability, reusability, scalability and robustness. There is no standard rule for using design patterns. There are some situations that a pattern is applied for a specific problem and this pattern uses another pattern. In this paper, we study the effect of using chain of patterns on software quality metrics.

Keywords: Design Patterns, Design patterns' Relationship, Software quality Metrics, Software Engineering.

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Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

Abstract:

In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution.

Keywords: Multi-objective optimization, random drift particle swarm optimization, crowding distance, Pareto optimal solution.

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Authors: Ö. Şenyiğit, A. Çolak

Abstract:

It is of great importance for an architectural student to know the parameters through which he/she can conduct his/her design and makes his/her design effective in architectural education. Therefore; an empirical application study was carried out through the designing activity using the emulation model to support the design and design approaches of architectural students. During the investigation period, studies were done on the basic design elements and principles of the fall semester, and the emulation model, one of the designing methods that constitute the subject of the study, was fictionalized as three phased “recognition-interpretation-application”. As a result of the study, it was observed that when students were given a key method during the design process, their awareness increased and their aspects improved as well.

Keywords: Basic design, design education, design methods, emulation.

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Authors: Meemongkol A., Tipsuwanporn V., Numsomran A.

Abstract:

The authors present optimization parameters of rotary positioner controller in hard disk drive servo track writing process using coefficient diagram method; CDM. Due to estimation parameters in PI Positioning Control System by expected ratio method cannot meet the required specification of response effectively, we suggest coefficient diagram method for defining controller parameters under the requirement of the system. Finally, the simulation results show that our proposed method can improve the problem in tuning parameter of rotary positioner controller. It is satisfied specification of performance of control system. Furthermore, it is very convenient as a fast adjustment damping ratio as well as a high speed response.

Keywords: Optimization Parameters, Rotary Positioner, CDM

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Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon

Abstract:

Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.

Keywords: Exergy analysis, Genetic algorithm, Rankine cycle, Single and Multi-objective function.

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Authors: B. Jabbari, N. Tahouni, M. H. Panjeshahi

Abstract:

In this study the integration of an absorption heat pump (AHP) with the concentration section of an industrial pulp and paper process is investigated using pinch technology. The optimum design of the proposed water-lithium bromide AHP is then achieved by minimizing the total annual cost. A comprehensive optimization is carried out by relaxation of all stream pressure drops as well as heat exchanger areas involving in AHP structure. It is shown that by applying genetic algorithm optimizer, the total annual cost of the proposed AHP is decreased by 18% compared to one resulted from simulation.

Keywords: Absorption Heat Pump, Genetic Algorithm, Kraft Industry, Pinch Technology

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Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.

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Authors: Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay

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Optimal reactive power flow is an optimization problem with one or more objective of minimizing the active power losses for fixed generation schedule. The control variables are generator bus voltages, transformer tap settings and reactive power output of the compensating devices placed on different bus bars. Biogeography- Based Optimization (BBO) technique has been applied to solve different kinds of optimal reactive power flow problems subject to operational constraints like power balance constraint, line flow and bus voltages limits etc. BBO searches for the global optimum mainly through two steps: Migration and Mutation. In the present work, BBO has been applied to solve the optimal reactive power flow problems on IEEE 30-bus and standard IEEE 57-bus power systems for minimization of active power loss. The superiority of the proposed method has been demonstrated. Considering the quality of the solution obtained, the proposed method seems to be a promising one for solving these problems.

Keywords: Active Power Loss, Biogeography-Based Optimization, Migration, Mutation, Optimal Reactive Power Flow.

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Authors: R. Damaševičius

Abstract:

System-level design based on high-level abstractions is becoming increasingly important in hardware and embedded system design. This paper analyzes meta-design techniques oriented at developing meta-programs and meta-models for well-understood domains. Meta-design techniques include meta-programming and meta-modeling. At the programming level of design process, metadesign means developing generic components that are usable in a wider context of application than original domain components. At the modeling level, meta-design means developing design patterns that describe general solutions to the common recurring design problems, and meta-models that describe the relationship between different types of design models and abstractions. The paper describes and evaluates the implementation of meta-design in hardware design domain using object-oriented and meta-programming techniques. The presented ideas are illustrated with a case study.

Keywords: Design patterns, meta-design, meta-modeling, metaprogramming.

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Authors: Samad Nejatian, Vahideh Rezaie, Vahid Asadpour

Abstract:

This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.

Keywords: fuzzy system, low noise amplifier, microwaveamplifier, space mapping

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Authors: Farhad Kolahan, Mohammad Bironro

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This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.

Keywords: Regression modeling, PMEDM, GeneticAlgorithm, Optimization.

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Authors: Mehrdad N. Khajavi, Bahram Notghi, Golamhassan Paygane

Abstract:

Vehicle suspension design must fulfill some conflicting criteria. Among those is ride comfort which is attained by minimizing the acceleration transmitted to the sprung mass, via suspension spring and damper. Also good handling of a vehicle is a desirable property which requires stiff suspension and therefore is in contrast with a vehicle with good ride. Among the other desirable features of a suspension is the minimization of the maximum travel of suspension. This travel which is called suspension working space in vehicle dynamics literature is also a design constraint and it favors good ride. In this research a full car 8 degrees of freedom model has been developed and the three above mentioned criteria, namely: ride, handling and working space has been adopted as objective functions. The Multi Objective Programming (MOP) discipline has been used to find the Pareto Front and some reasoning used to chose a design point between these non dominated points of Pareto Front.

Keywords: Vehicle, Ride, Handling, Suspension, Working Space, Multi Objective Programming.

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