Search results for: optimization criterion.

Authors: Florian Gschösser, Walter Purrer

Abstract:

The paper shows examples for the (environmental) optimization of production processes for asphalt mixtures applied for typical road pavements in Austria and Switzerland. The conducted “from-cradle-to-gate” LCA firstly analyzes the production one cubic meter of asphalt and secondly all material production processes for exemplary highway pavements applied in Austria and Switzerland. It is shown that environmental impacts can be reduced by the application of reclaimed asphalt pavement (RAP) and by the optimization of specific production characteristics, e.g. the reduction of the initial moisture of the mineral aggregate and the reduction of the mixing temperature by the application of low-viscosity and foam bitumen. The results of the LCA study demonstrate reduction potentials per cubic meter asphalt of up to 57 % (Global Warming Potential–GWP) and 77 % (Ozone depletion–ODP). The analysis per square meter of asphalt pavement determined environmental potentials of up to 40 % (GWP) and 56 % (ODP).

Keywords: Asphalt mixtures, environmental potentials, life cycle assessment, material production.

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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: A. Mohajer, A. Noroozi, S. Norouzi

Abstract:

The bypass exhaust system of a 160 MW combined cycle has been modeled and analyzed using numerical simulation in 2D prospective. Analysis was carried out using the commercial numerical simulation software, FLUENT 6.2. All inputs were based on the technical data gathered from working conditions of a Siemens V94.2 gas turbine, installed in the Yazd power plant. This paper deals with reduction of pressure drop in bypass exhaust system using turning vanes mounted in diverter box in order to alleviate turbulent energy dissipation rate above diverter box. The geometry of such turning vanes has been optimized based on the flow pattern at diverter box inlet. The results show that the use of optimized turning vanes in diverter box can improve the flow pattern and eliminate vortices around sharp edges just before the silencer. Furthermore, this optimization could decrease the pressure drop in bypass exhaust system and leads to higher plant efficiency.

Keywords: Numerical simulation, Diverter box, Turning vanes, Exhaust system

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Authors: Sandeep Kaur Chouhan, Jatinderdeep Kaur, S. S. Bhatia

Abstract:

The existence of sine and cosine series as a Fourier series, their L1-convergence seems to be one of the difficult question in theory of convergence of trigonometric series in L1-metric norm. In the literature so far available, various authors have studied the L1-convergence of cosine and sine trigonometric series with special coefficients. In this paper, we present a modified cosine and sine sums and criterion for L1-convergence of these modified sums is obtained. Also, a necessary and sufficient condition for the L1-convergence of the cosine and sine series is deduced as corollaries.

Keywords: Conjugate Dirichlet kernel, Dirichlet kernel, L1-convergence, modified sums.

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Authors: Bogdan Walek, Cyril Klimes

Abstract:

This paper focuses on testing database of existing information system. At the beginning we describe the basic problems of implemented databases, such as data redundancy, poor design of database logical structure or inappropriate data types in columns of database tables. These problems are often the result of incorrect understanding of the primary requirements for a database of an information system. Then we propose an algorithm to compare the conceptual model created from vague requirements for a database with a conceptual model reconstructed from implemented database. An algorithm also suggests steps leading to optimization of implemented database. The proposed algorithm is verified by an implemented prototype. The paper also describes a fuzzy system which works with the vague requirements for a database of an information system, procedure for creating conceptual from vague requirements and an algorithm for reconstructing a conceptual model from implemented database.

Keywords: testing, database, relational database, information system, conceptual model, fuzzy, uncertain information, database testing, reconstruction, requirements, optimization

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Authors: A. M. El Ansary, A. A. El Damatty, A. O. Nassef

Abstract:

The aim of the current study is to develop a numerical tool that is capable of achieving an optimum shape and design of hyperbolic cooling towers based on coupling a non-linear finite element model developed in-house and a genetic algorithm optimization technique. The objective function is set to be the minimum weight of the tower. The geometric modeling of the tower is represented by means of B-spline curves. The finite element method is applied to model the elastic buckling behaviour of a tower subjected to wind pressure and dead load. The study is divided into two main parts. The first part investigates the optimum shape of the tower corresponding to minimum weight assuming constant thickness. The study is extended in the second part by introducing the shell thickness as one of the design variables in order to achieve an optimum shape and design. Design, functionality and practicality constraints are applied.

Keywords: B-splines, Cooling towers, Finite element, Genetic algorithm, Optimization

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

Abstract:

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: Dynamic system modeling, neural network, normal equation, second order gradient descent.

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Authors: Ghanima Al-Sharrah, Haitham M. Lababidi, Yusuf I. Ali

Abstract:

The main objective of the current work is to introduce sustainability factors in optimizing the supply chain model for process industries. The supply chain models are normally based on purely economic considerations related to costs and profits. To account for sustainability, two additional factors have been introduced; environment and risk. A supply chain for an entire petroleum organization has been considered for implementing and testing the proposed optimization models. The environmental and risk factors were introduced as indicators reflecting the anticipated impact of the optimal production scenarios on sustainability. The aggregation method used in extending the single objective function to multi-objective function is proven to be quite effective in balancing the contribution of each objective term. The results indicate that introducing sustainability factor would slightly reduce the economic benefit while improving the environmental and risk reduction performances of the process industries.

Keywords: Supply chain, optimization, LP models, risk, environmental indicators, multi-objective.

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Authors: Tawiwat Veeraklaew, Nathasit Phathana-im, Songkit Heama

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting relationship between the minimum direct and indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of direct and indirect jerks are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of control inputs employed by minimum direct and indirect jerk designs. By considering minimum indirect jerk problem, the numerical solution becomes much easier and yields to the similar results as minimum direct jerk problem.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: Hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation.

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Authors: V. Tawiwat, P. Jumnong

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting when combining the minimum energy and jerk of indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of the minimum energy, the minimum jerk and combining them together are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of state inputs employed by combining minimum energy and jerk designs. The numerical solution of minimum direct jerk and energy problem are exactly the same solution; however, the solutions from problem of minimum energy yield the similar solution especially in term of tendency.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: H. Shayeghi, M. Mahdavi

Abstract:

Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.

Keywords: Adequacy Optimization, Transmission Expansion Planning, DCGA.

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Authors: Changjin Xu, Yusen Wu

Abstract:

In this paper, applying frequency domain approach, a delayed competitive web-site system is investigated. By choosing the parameter α as a bifurcation parameter, it is found that Hopf bifurcation occurs as the bifurcation parameter α passes a critical values. That is, a family of periodic solutions bifurcate from the equilibrium when the bifurcation parameter exceeds a critical value. Some numerical simulations are included to justify the theoretical analysis results. Finally, main conclusions are given.

Keywords: Web-site system, stability, Nyquist criterion, Hopf bifurcation, frequency domain.

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Authors: Govind Shay Sharma, Randhir Singh Baghel

Abstract:

The stock management of raw materials and finished goods is a significant issue for industries in fulfilling customer demand. Optimization of inventory strategies is crucial to enhancing customer service, reducing lead times and costs, and meeting market demand. This paper suggests finding an approach to predict the optimum stock level by utilizing past stocks and forecasting the required quantities. In this paper, we utilized Artificial Neural Network (ANN) to determine the optimal value. The objective of this paper is to discuss the optimized ANN that can find the best solution for the inventory model. In the context of the paper, we mentioned that the k-means algorithm is employed to create homogeneous groups of items. These groups likely exhibit similar characteristics or attributes that make them suitable for being managed using uniform inventory control policies. The paper proposes a method that uses the neural fit algorithm to control the cost of inventory.

Keywords: Artificial Neural Network, inventory management, optimization, distributor center.

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Authors: Malek Makki

Abstract:

The main purpose of this research study is to assist non-profit organizations (NPOs) to better segment a group of least developing countries and to optimally target the most needier areas, so that the provided aids make positive and lasting differences. We applied international marketing and strategy approaches to segment a sub-group of candidates among a group of 151 countries identified by the UN-G77 list, and furthermore, we point out the areas of priorities. We use reliable and well known criteria on the basis of economics, geography, demography and behavioral. These criteria can be objectively estimated and updated so that a follow-up can be performed to measure the outcomes of any program. We selected 12 socio-economic criteria that complement each other: GDP per capita, GDP growth, industry value added, export per capita, fragile state index, corruption perceived index, environment protection index, ease of doing business index, global competitiveness index, Internet use, public spending on education, and employment rate. A weight was attributed to each variable to highlight the relative importance of each criterion within the country. Care was taken to collect the most recent available data from trusted well-known international organizations (IMF, WB, WEF, and WTO). Construct of equivalence was carried out to compare the same variables across countries. The combination of all these weighted estimated criteria provides us with a global index that represents the level of development per country. An absolute index that combines wars and risks was introduced to exclude or include a country on the basis of conflicts and a collapsing state. The final step applied to the included countries consists of a benchmarking method to select the segment of countries and the percentile of each criterion. The results of this study allowed us to exclude 16 countries for risks and security. We also excluded four countries because they lack reliable and complete data. The other countries were classified per percentile thru their global index, and we identified the needier and the areas where aids are highly required to help any NPO to prioritize the area of implementation. This new concept is based on defined, actionable, accessible and accurate variables by which NPO can implement their program and it can be extended to profit companies to perform their corporate social responsibility acts.

Keywords: Developing countries, International marketing, non-profit organization, segmentation.

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Authors: Jui-Sheng Lin, Yi-Sung Yang, Meei-Ling Hung, Teh-Lu Liao, Jun-Juh Yan

Abstract:

The global chaos synchronization for a class of time-delayed power systems is investigated via observer-based approach. By employing the concepts of quadratic stability theory and generalized system model, a new sufficient criterion for constructing an observer is deduced. In contrast to the previous works, this paper proposes a theoretical and systematic design procedure to realize chaos synchronization for master-slave power systems. Finally, an illustrative example is given to show the applicability of the obtained scheme.

Keywords: Chaos, Synchronization, Quadratic stability theory, Observer

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Authors: A. Safari, H. Shayeghi, H. A. Shayanfar

Abstract:

On the basis of the linearized Phillips-Herffron model of a single-machine power system, a novel method for designing unified power flow controller (UPFC) based output feedback controller is presented. The design problem of output feedback controller for UPFC is formulated as an optimization problem according to with the time domain-based objective function which is solved by iteration particle swarm optimization (IPSO) that has a strong ability to find the most optimistic results. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results prove the effectiveness and robustness of the proposed method in terms of a high performance power system. The simulation study shows that the designed controller by Iteration PSO performs better than Classical PSO in finding the solution.

Keywords: UPFC, IPSO, output feedback Controller.

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Authors: Atefeh Pourshafie, Mohsen. Saniei, S. S. Mortazavi, A. Saeedian

Abstract:

In this paper optimal capacitor placement problem has been formulated in a restructured distribution network. In this scenario the distribution network operator can consider reactive energy also as a service that can be sold to transmission system. Thus search for optimal location, size and number of capacitor banks with the objective of loss reduction, maximum income from selling reactive energy to transmission system and return on investment for capacitors, has been performed. Results is influenced with economic value of reactive energy, therefore problem has been solved for various amounts of it. The implemented optimization technique is genetic algorithm. For any value of reactive power economic value, when reverse of investment index increase and change from zero or negative values to positive values, the threshold value of selling reactive power has been obtained. This increasing price of economic parameter is reasonable until the network losses is less than loss before compensation.

Keywords: capacitor placement, deregulated electric market, distribution network optimization.

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Authors: Maatoug Hassine, Mourad Hrizi

Abstract:

In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: Geometric inverse source problem, heat equation, topological sensitivity, topological optimization, Kohn-Vogelius formulation.

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Authors: F. Gökgöz, M. E. Atmaca

Abstract:

Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: Electricity market, portfolio optimization, risk management in electricity market, Sharpe ratio.

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Authors: Khashayar Kashani Jou

Abstract:

Walking as a type of non-motorized transportation has various social, economical and environmental privileges. Also, today different aspects of sustainable development have been emphasized and promotion of sustainable transportation modes has been considered according to this approach. Therefore, the objective of this research is exploring the circumstance of relationship between walking and sustainable urban transportation.For writing this article, the most important resources related to the traits of walking have been surveyed via a documentary method and after explaining the concept of sustainable transportation and its indicators, benefiting from the viewpoints of transportation experts of Tehran, as the capital and greatest city of Iran, different modes of urban transportation have been compared in proportion to each criterion and to each other and have been analyzed according to AHP method. The results of this study indicate that walking is the most sustainable mode of inner city transportation.

Keywords: Walking, Non-motorized transportation, Sustainable transportation, AHP

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Authors: Kyaw Myo Lin, Pyone Lai Swe, Khine Zin Oo

Abstract:

In this paper, an approach combining analytical method for the distributed generator (DG) sizing and meta-heuristic search for the optimal location of DG has been presented. The optimal size of DG on each bus is estimated by the loss sensitivity factor method while the optimal sites are determined by Particle Swarm Optimization (PSO) based optimal reactive power dispatch for minimizing active power loss. To confirm the proposed approach, it has been tested on IEEE-30 bus test system. The adjustments of operating constraints and voltage profile improvements have also been observed. The obtained results show that the allocation of DGs results in a significant loss reduction with good voltage profiles and the combined approach is competent in keeping the system voltages within the acceptable limits.

Keywords: Analytical approach, distributed generations, optimal size, optimal location, optimal reactive power dispatch, particle swarm optimization algorithm.

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Authors: Kamil Aida-zade, C. Ardil

Abstract:

We study the problem of synthesis of lumped sources control for the objects with distributed parameters on the basis of continuous observation of phase state at given points of object. In the proposed approach the phase state space (phase space) is beforehand somehow partitioned at observable points into given subsets (zones). The synthesizing control actions therewith are taken from the class of piecewise constant functions. The current values of control actions are determined by the subset of phase space that contains the aggregate of current states of object at the observable points (in these states control actions take constant values). In the paper such synthesized control actions are called zone control actions. A technique to obtain optimal values of zone control actions with the use of smooth optimization methods is given. With this aim, the formulas of objective functional gradient in the space of zone control actions are obtained.

Keywords: Feedback control, distributed systems, smooth optimization methods, lumped control synthesis.

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Authors: Andrej Miklošík, Petra Horváthová, Štefan Žák

Abstract:

Nowadays companies in all sectors are looking for the sources of competitive advantages. Holistic marketing approach searches for their emergence based on the integration of all components and elements across the organization. Modern marketing sees the sources of competitive advantage in implementing the latest managerial practices, motivation, intelligent project management, knowledge management, collaborative marketing, CSR and, in the recent years, also in the business process optimization. With the use of modern tools including business process management and business process modelling the company can markedly increase its internal efficiency which can lead not only to lowering the costs but to creating the environment for optimal customer care, positive corporate culture and for origination of innovations as well. In the article the authors analyze the recent trend in this area and introduce suggestions to companies to identify and optimize the key processes that have a significant impact of the company´s competitiveness.

Keywords: business process optimization, competitive advantage, corporate social responsibility, knowledge management

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Authors: Miaomiao Yang, Shouming Zhong

Abstract:

This paper studies the problem of exponential stability analysis for recurrent neural networks with time-varying delay.By establishing a suitable augmented LyapunovCKrasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system.In order to get a less conservative results of the condition,zero equalities and reciprocally convex approach are employed. The several exponential stability criterion proposed in this paper is simpler and effective. A numerical example is provided to demonstrate the feasibility and effectiveness of our results.

Keywords: Exponential stability , Neural networks, Linear matrix inequality, Lyapunov-Krasovskii, Time-varying.

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Authors: K. M. Oba

Abstract:

The transportation modelling technique was adopted in the solution of the problem of transportation of Plaster of Paris (POP) cement from three supply locations (construction materials markets) to three demand locations (construction sites) in Port Harcourt. The study was carried out for 40 kg bags of POP cement fully loaded on 600 bags per truck from the three selected construction materials markets in Port Harcourt. The costs of transporting the POP cement were determined and subjected to the North-West Corner, Least Cost, and Vogel’s approximation methods to determine the initial feasible solution. Of the three results, the Least Cost Method turned out to have the lowest cost. Using the Stepping Stone Method, the optimum shipping cost was finally attained after two successive iterations. The optimum shipping cost was calculated to be $1,690 or ₦1,774,500 as of October 2023. As a result of this study, the application of transportation modelling can boost the effective management of the transportation of POP cement in construction projects.

Keywords: Cost of POP cement, management of transportation, optimization of shipping cost, Plaster of Paris, transportation model.

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Authors: O. S. Ebrahim, M. A. Badr, Kh. H. Gharib, H. K. Temraz

Abstract:

This paper presents a methodology based on genetic algorithm (GA) to tune the parameters of proportional-integral-differential (PID) controllers utilized in the automatic voltage regulator (AVR) and speed governor of a brushless synchronous generator driven by three-stage steam turbine. The parameter tuning is represented as a nonlinear optimization problem solved by GA to minimize the integral of absolute error (IAE). The problem of integral windup due to physical system limitations is solved using simple anti-windup scheme. The obtained controllers are compared to those designed using classical Ziegler-Nichols technique and constrained optimization. Results show distinct superiority of the proposed method.

Keywords: Brushless synchronous generator, Genetic Algorithm, GA, Proportional-Integral-Differential control, PID control, automatic voltage regulator, AVR.

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Authors: Muhammad Hazwan H., Azlina M.F., Hasfalina C.M., Zurina Z.A., Hishamuddin J

Abstract:

Gaharu that produced by Aquilaria spp. is classified as one of the most valuable forest products traded internationally as it is very resinous, fragrant and highly valuable heartwood. Gaharu has been widely used in aromatheraphy, medicine, perfume and religious practices. This work aimed to determine the factors affecting solid liquid extraction of gaharu oil using hexane as solvent under experimental condition. The kinetics of extraction was assumed and verified based on a second-order mechanism. The effect of three main factors, which were temperature, reaction time and solvent to solid ratio were investigated to achieve maximum oil yield. The optimum condition were found at temperature 65°C, 9 hours reaction time and solvent to solid ratio of 12:1 with 14.5% oil yield. The kinetics experimental data agrees and well fitted with the second order extraction model. The initial extraction rate (h) was 0.0115 gmL-1min-1; the extraction capacity (Cs) was 1.282gmL-1; the second order extraction constant (k) was 0.007 mLg-1min-1 and coefficient of determination, R2 was 0.945.

Keywords: Gaharu, solid liquid extraction, optimization, kinetics.

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Authors: Seongmin Yim, Hyun-Kyu Kang

Abstract:

As a part of evaluation system for R&D program, the Korean government has applied feasibility analysis since 2008. Various professionals put forth a great effort in order to catch up the high degree of freedom of R&D programs, and make contributions to evolving the feasibility analysis. We analyze diverse R&D programs from various viewpoints, such as technology, policy, and Economics, integrate the separate analysis, and finally arrive at a definite result; whether a program is feasible or unfeasible. This paper describes the concept and method of the feasibility analysis as a decision making tool. The analysis unit and content of each criterion, which are key elements in a comprehensive decision making structure, are examined

Keywords: Decision Making of New Government R&D Program, Feasibility Analysis Study

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Authors: F. Gökgöz, M. E. Atmaca

Abstract:

Electricity has an indispensable role in human daily life, technological development and economy. It is a special product or service that should be instantaneously generated and consumed. Sources of the world are limited so that effective and efficient use of them is very important not only for human life and environment but also for technological and economic development. Competitive electricity market is one of the important way that provides suitable platform for effective and efficient use of electricity. Besides benefits, it brings along some risks that should be carefully managed by a market player like Electricity Generation Company. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Value at Risk methods for case studies. Performance of optimal electricity sale solutions are measured and the portfolio performance has been evaluated via Sharpe-Ratio, and compared with conventional approach. Biennial historical electricity price data of Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: Electricity market, portfolio optimization, risk management, Sharpe ratio, value at risk.

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