Search results for: Optimization rateand Blocking Probability.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2401

Search results for: Optimization rateand Blocking Probability.

2161 Bee Colony Optimization Applied to the Bin Packing Problem

Authors: Kenza Aida Amara, Bachir Djebbar

Abstract:

We treat the two-dimensional bin packing problem which involves packing a given set of rectangles into a minimum number of larger identical rectangles called bins. This combinatorial problem is NP-hard. We propose a pretreatment for the oriented version of the problem that allows the valorization of the lost areas in the bins and the reduction of the size problem. A heuristic method based on the strategy first-fit adapted to this problem is presented. We present an approach of resolution by bee colony optimization. Computational results express a comparison of the number of bins used with and without pretreatment.

Keywords: Bee colony optimization, bin packing, heuristic algorithm, pretreatment.

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2160 A Mahalanobis Distance-based Diversification and Nelder-Mead Simplex Intensification Search Scheme for Continuous Ant Colony Optimization

Authors: Sasadhar Bera, Indrajit Mukherjee

Abstract:

Ant colony optimization (ACO) and its variants are applied extensively to resolve various continuous optimization problems. As per the various diversification and intensification schemes of ACO for continuous function optimization, researchers generally consider components of multidimensional state space to generate the new search point(s). However, diversifying to a new search space by updating only components of the multidimensional vector may not ensure that the new point is at a significant distance from the current solution. If a minimum distance is not ensured during diversification, then there is always a possibility that the search will end up with reaching only local optimum. Therefore, to overcome such situations, a Mahalanobis distance-based diversification with Nelder-Mead simplex-based search scheme for each ant is proposed for the ACO strategy. A comparative computational run results, based on nine nonlinear standard test problems, confirms that the performance of ACO is improved significantly with the integration of the proposed schemes in the ACO.

Keywords: Ant Colony Optimization, Diversification Scheme, Intensification, Mahalanobis Distance, Nelder-Mead Simplex.

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2159 A Fuzzy Satisfactory Optimization Method Based on Stress Analysis for a Hybrid Composite Flywheel

Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren

Abstract:

Considering the cost evaluation and the stress analysis, a fuzzy satisfactory optimization (FSO) method has been developed for a hybrid composite flywheel. To evaluate the cost, the cost coefficients of the flywheel components are obtained through calculating the weighted sum of the scores of the material manufacturability, the structure character, and the material price. To express the satisfactory degree of the energy, the cost, and the mass, the satisfactory functions are proposed by using the decline function and introducing a satisfactory coefficient. To imply the different significance of the objectives, the object weight coefficients are defined. Based on the stress analysis of composite material, the circumferential and radial stresses are considered into the optimization formulation. The simulations of the FSO method with different weight coefficients and storage energy density optimization (SEDO) method of a flywheel are contrasted. The analysis results show that the FSO method can satisfy different requirements of the designer and the FSO method with suitable weight coefficients can replace the SEDO method.

Keywords: Flywheel energy storage, fuzzy, optimization, stress analysis.

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2158 Improving Flash Flood Forecasting with a Bayesian Probabilistic Approach: A Case Study on the Posina Basin in Italy

Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: Flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina.

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2157 Comparative Analysis of Two Modeling Approaches for Optimizing Plate Heat Exchangers

Authors: Fábio A. S. Mota, Mauro A. S. S. Ravagnani, E. P. Carvalho

Abstract:

In the present paper the design of plate heat exchangers is formulated as an optimization problem considering two mathematical modelling. The number of plates is the objective function to be minimized, considering implicitly some parameters configuration. Screening is the optimization method used to solve the problem. Thermal and hydraulic constraints are verified, not viable solutions are discarded and the method searches for the convergence to the optimum, case it exists. A case study is presented to test the applicability of the developed algorithm. Results show coherency with the literature.

Keywords: Plate heat exchanger, optimization, modeling, simulation.

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2156 Optimization of Lakes Aeration Process

Authors: Mohamed Abdelwahed

Abstract:

The aeration process via injectors is used to combat the lack of oxygen in lakes due to eutrophication. A 3D numerical simulation of the resulting flow using a simplified model is presented. In order to generate the best dynamic in the fluid with respect to the aeration purpose, the optimization of the injectors location is considered. We propose to adapt to this problem the topological sensitivity analysis method which gives the variation of a criterion with respect to the creation of a small hole in the domain. The main idea is to derive the topological sensitivity analysis of the physical model with respect to the insertion of an injector in the fluid flow domain. We propose in this work a topological optimization algorithm based on the studied asymptotic expansion. Finally we present some numerical results, showing the efficiency of our approach

Keywords: Quasi Stokes equations, Numerical simulation, topological optimization, sensitivity analysis.

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2155 Robust Design of Power System Stabilizers Using Adaptive Genetic Algorithms

Authors: H. Alkhatib, J. Duveau

Abstract:

Genetic algorithms (GAs) have been widely used for global optimization problems. The GA performance depends highly on the choice of the search space for each parameter to be optimized. Often, this choice is a problem-based experience. The search space being a set of potential solutions may contain the global optimum and/or other local optimums. A bad choice of this search space results in poor solutions. In this paper, our approach consists in extending the search space boundaries during the GA optimization, only when it is required. This leads to more diversification of GA population by new solutions that were not available with fixed search space boundaries. So, these dynamic search spaces can improve the GA optimization performances. The proposed approach is applied to power system stabilizer optimization for multimachine power system (16-generator and 68-bus). The obtained results are evaluated and compared with those obtained by ordinary GAs. Eigenvalue analysis and nonlinear system simulation results show the effectiveness of the proposed approach to damp out the electromechanical oscillation and enhance the global system stability.

Keywords: Genetic Algorithms, Multiobjective Optimization, Power System Stabilizer, Small Signal Stability.

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2154 Economic Dispatch Fuzzy Linear Regression and Optimization

Authors: A. K. Al-Othman

Abstract:

This study presents a new approach based on Tanaka's fuzzy linear regression (FLP) algorithm to solve well-known power system economic load dispatch problem (ELD). Tanaka's fuzzy linear regression (FLP) formulation will be employed to compute the optimal solution of optimization problem after linearization. The unknowns are expressed as fuzzy numbers with a triangular membership function that has middle and spread value reflected on the unknowns. The proposed fuzzy model is formulated as a linear optimization problem, where the objective is to minimize the sum of the spread of the unknowns, subject to double inequality constraints. Linear programming technique is employed to obtain the middle and the symmetric spread for every unknown (power generation level). Simulation results of the proposed approach will be compared with those reported in literature.

Keywords: Economic Dispatch, Fuzzy Linear Regression (FLP)and Optimization.

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2153 Stochastic Risk Analysis Framework for Building Construction Projects

Authors: Abdulkadir Abu Lawal

Abstract:

The study was carried out to establish the probability density function of some selected building construction projects of similar complexity delivered using Bill of Quantities (BQ) and Lump Sum (LS) forms of contract, and to draw a reliability scenario for each form of contract. 30 of such delivered projects are analyzed for each of the contract forms using Weibull Analysis, and their Weibull functions (α, and β) are determined based on their completion times. For the BQ form of contract delivered projects, α is calculated as 1.6737E20 and β as + 0.0115 and for the LS form, α is found to be 5.6556E03 and β is determined as + 0.4535. Using these values, respective probability density functions are calculated and plotted, as handy tool for risk analysis of future projects of similar characteristics. By input of variables from other projects, decision making processes can be made for a whole project or its components using EVM Analysis in project evaluation and review techniques. This framework, as a quantitative approach, depends on the assumption of normality in projects completion time, it can help greatly in determining the completion time probability for veritable projects using any of the contract forms under consideration. Projects aspects that are not amenable to measurement, on the other hand, can be analyzed using fuzzy sets and fuzzy logic. This scenario can be drawn for different types of building construction projects, and using different suitable forms of contract in projects delivery.

Keywords: Building construction, Projects, Forms of contract, Probability density function, Reliability scenario.

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2152 Application of Particle Swarm Optimization Technique for an Optical Fiber Alignment System

Authors: Marc Landry, Azeddine Kaddouri, Yassine Bouslimani, Mohsen Ghribi

Abstract:

In this paper, a new alignment method based on the particle swarm optimization (PSO) technique is presented. The PSO algorithm is used for locating the optimal coupling position with the highest optical power with three-degrees of freedom alignment. This algorithm gives an interesting results without a need to go thru the complex mathematical modeling of the alignment system. The proposed algorithm is validated considering practical tests considering the alignment of two Single Mode Fibers (SMF) and the alignment of SMF and PCF fibers.

Keywords: Particle-swarm optimization, optical fiber, automatic alignment.

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2151 Performance of Soft Handover Algorithm in Varied Propagation Environments

Authors: N. P. Singh, Brahmjit Singh

Abstract:

CDMA cellular networks support soft handover, which guarantees the continuity of wireless services and enhanced communication quality. Cellular networks support multimedia services under varied propagation environmental conditions. In this paper, we have shown the effect of characteristic parameters of the cellular environments on the soft handover performance. We consider path loss exponent, standard deviation of shadow fading and correlation coefficient of shadow fading as the characteristic parameters of the radio propagation environment. A very useful statistical measure for characterizing the performance of mobile radio system is the probability of outage. It is shown through numerical results that above parameters have decisive effect on the probability of outage and hence the overall performance of the soft handover algorithm.

Keywords: CDMA, Correlation coefficient, Path loss exponent, Probability of outage, Soft handover.

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2150 Economic Load Dispatch with Daily Load Patterns and Generator Constraints by Particle Swarm Optimization

Authors: N. Phanthuna V. Phupha N. Rugthaicharoencheep, S. Lerdwanittip

Abstract:

This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction

Keywords: Particle Swarm Optimization, Economic Load Dispatch, Generator Constraints.

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2149 An Optimization Analysis on an Automotive Component with Fatigue Constraint Using HyperWorks Software for Environmental Sustainability

Authors: W. M. Wan Muhamad, E. Sujatmika, M.R. Idris, S.A. Syed Ahmad

Abstract:

A finite element analysis (FEA) computer software HyperWorks is utilized in re-designing an automotive component to reduce its mass. Reduction of components mass contributes towards environmental sustainability by saving world-s valuable metal resources and by reducing carbon emission through improved overall vehicle fuel efficiency. A shape optimization analysis was performed on a rear spindle component. Pre-processing and solving procedures were performed using HyperMesh and RADIOSS respectively. Shape variables were defined using HyperMorph. Then optimization solver OptiStruct was utilized with fatigue life set as a design constraint. Since Stress-Number of Cycle (S-N) theory deals with uni-axial stress, the Signed von Misses stress on the component was used for looking up damage on S-N curve, and Gerber criterion for mean stress corrections. The optimization analysis resulted in mass reduction of 24% of the original mass. The study proved that the adopted approach has high potential use for environmental sustainability.

Keywords: Environmental Sustainability, Shape Optimization, Fatigue, Rear Spindle.

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2148 Parametric Modeling Approach for Call Holding Times for IP based Public Safety Networks via EM Algorithm

Authors: Badarch Tuyatsetseg

Abstract:

This paper presents parametric probability density models for call holding times (CHTs) into emergency call center based on the actual data collected for over a week in the public Emergency Information Network (EIN) in Mongolia. When the set of chosen candidates of Gamma distribution family is fitted to the call holding time data, it is observed that the whole area in the CHT empirical histogram is underestimated due to spikes of higher probability and long tails of lower probability in the histogram. Therefore, we provide the Gaussian parametric model of a mixture of lognormal distributions with explicit analytical expressions for the modeling of CHTs of PSNs. Finally, we show that the CHTs for PSNs are fitted reasonably by a mixture of lognormal distributions via the simulation of expectation maximization algorithm. This result is significant as it expresses a useful mathematical tool in an explicit manner of a mixture of lognormal distributions.

Keywords: A mixture of lognormal distributions, modeling call holding times, public safety network.

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2147 Cognitive Relaying in Interference Limited Spectrum Sharing Environment: Outage Probability and Outage Capacity

Authors: Md Fazlul Kader, Soo Young Shin

Abstract:

In this paper, we consider a cognitive relay network (CRN) in which the primary receiver (PR) is protected by peak transmit power ¯PST and/or peak interference power Q constraints. In addition, the interference effect from the primary transmitter (PT) is considered to show its impact on the performance of the CRN. We investigate the outage probability (OP) and outage capacity (OC) of the CRN by deriving closed-form expressions over Rayleigh fading channel. Results show that both the OP and OC improve by increasing the cooperative relay nodes as well as when the PT is far away from the SR.

Keywords: Cognitive relay, outage, interference limited, decode-and-forward (DF).

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2146 Voltage Stability Enhancement Using Cat Swarm Optimization Algorithm

Authors: P. Suryakumari, P. Kantarao

Abstract:

Optimal Power Flow (OPF) problem in electrical power system is considered as a static, non-linear, multi-objective or a single objective optimization problem. This paper presents an algorithm for solving the voltage stability objective reactive power dispatch problem in a power system .The proposed approach employs cat swarm optimization algorithm for optimal settings of RPD control variables. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. CSO algorithm is tested on standard IEEE 30 bus system and the results are compared with other methods to prove the effectiveness of the new algorithm. As a result, the proposed method is the best for solving optimal reactive power dispatch problem.

Keywords: RPD problem, voltage stability enhancement, CSO algorithm.

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2145 Modeling Default Probabilities of the Chosen Czech Banks in the Time of the Financial Crisis

Authors: Petr Gurný

Abstract:

One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the creditscoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: Credit-scoring Models, Multidimensional Subordinated Lévy Model, Probability of Default.

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2144 A Discrete Choice Modeling Approach to Modular Systems Design

Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The paper proposes an approach for design of modular systems based on original technique for modeling and formulation of combinatorial optimization problems. The proposed approach is described on the example of personal computer configuration design. It takes into account the existing compatibility restrictions between the modules and can be extended and modified to reflect different functional and users- requirements. The developed design modeling technique is used to formulate single objective nonlinear mixedinteger optimization tasks. The practical applicability of the developed approach is numerically tested on the basis of real modules data. Solutions of the formulated optimization tasks define the optimal configuration of the system that satisfies all compatibility restrictions and user requirements.

Keywords: Constrained discrete combinatorial choice, modular systems design, optimization problem, PC configuration.

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2143 A Holistic Approach for Technical Product Optimization

Authors: H. Lang, M. Bader, A. Buchroithner

Abstract:

Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: Design, product development, product optimization, systems engineering, flywheel energy storage.

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2142 Optimal Design of UPFC Based Damping Controller Using Iteration PSO

Authors: Amin Safari, Hossein Shayeghi

Abstract:

This paper presents a novel approach for tuning unified power flow controller (UPFC) based damping controller in order to enhance the damping of power system low frequency oscillations. The design problem of damping controller is formulated as an optimization problem according to the eigenvalue-based objective function which is solved using iteration particle swarm optimization (IPSO). The effectiveness of the proposed controller is demonstrated through eigenvalue analysis and nonlinear time-domain simulation studies under a wide range of loading conditions. The simulation study shows that the designed controller by IPSO performs better than CPSO in finding the solution. Moreover, the system performance analysis under different operating conditions show that the δE based controller is superior to the mB based controller.

Keywords: UPFC, Optimization Problem, Iteration ParticleSwarm Optimization, Damping Controller, Low FrequencyOscillations.

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2141 Optimization of Fuzzy Cluster Nodes in Cellular Multimedia Networks

Authors: J. D. Mallapur, Supriya H., Santosh B. K., Tej H.

Abstract:

The cellular network is one of the emerging areas of communication, in which the mobile nodes act as member for one base station. The cluster based communication is now an emerging area of wireless cellular multimedia networks. The cluster renders fast communication and also a convenient way to work with connectivity. In our scheme we have proposed an optimization technique for the fuzzy cluster nodes, by categorizing the group members into three categories like long refreshable member, medium refreshable member and short refreshable member. By considering long refreshable nodes as static nodes, we compute the new membership values for the other nodes in the cluster. We compare their previous and present membership value with the threshold value to categorize them into three different members. By which, we optimize the nodes in the fuzzy clusters. The simulation results show that there is reduction in the cluster computational time and iterational time after optimization.

Keywords: Clusters, fuzzy and optimization.

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2140 Probability Distribution of Rainfall Depth at Hourly Time-Scale

Authors: S. Dan'azumi, S. Shamsudin, A. A. Rahman

Abstract:

Rainfall data at fine resolution and knowledge of its characteristics plays a major role in the efficient design and operation of agricultural, telecommunication, runoff and erosion control as well as water quality control systems. The paper is aimed to study the statistical distribution of hourly rainfall depth for 12 representative stations spread across Peninsular Malaysia. Hourly rainfall data of 10 to 22 years period were collected and its statistical characteristics were estimated. Three probability distributions namely, Generalized Pareto, Exponential and Gamma distributions were proposed to model the hourly rainfall depth, and three goodness-of-fit tests, namely, Kolmogorov-Sminov, Anderson-Darling and Chi-Squared tests were used to evaluate their fitness. Result indicates that the east cost of the Peninsular receives higher depth of rainfall as compared to west coast. However, the rainfall frequency is found to be irregular. Also result from the goodness-of-fit tests show that all the three models fit the rainfall data at 1% level of significance. However, Generalized Pareto fits better than Exponential and Gamma distributions and is therefore recommended as the best fit.

Keywords: Goodness-of-fit test, Hourly rainfall, Malaysia, Probability distribution.

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2139 Building Gabor Filters from Retinal Responses

Authors: Johannes Partzsch, Christian Mayr, Rene Schuffny

Abstract:

Starting from a biologically inspired framework, Gabor filters were built up from retinal filters via LMSE algorithms. Asubset of retinal filter kernels was chosen to form a particular Gabor filter by using a weighted sum. One-dimensional optimization approaches were shown to be inappropriate for the problem. All model parameters were fixed with biological or image processing constraints. Detailed analysis of the optimization procedure led to the introduction of a minimization constraint. Finally, quantization of weighting factors was investigated. This resulted in an optimized cascaded structure of a Gabor filter bank implementation with lower computational cost.

Keywords: Gabor filter, image processing, optimization

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2138 Combining Ant Colony Optimization and Dynamic Programming for Solving a Dynamic Facility Layout Problem

Authors: A. Udomsakdigool, S. Bangsaranthip

Abstract:

This paper presents an algorithm which combining ant colony optimization in the dynamic programming for solving a dynamic facility layout problem. The problem is separated into 2 phases, static and dynamic phase. In static phase, ant colony optimization is used to find the best ranked of layouts for each period. Then the dynamic programming (DP) procedure is performed in the dynamic phase to evaluate the layout set during multi-period planning horizon. The proposed algorithm is tested over many problems with size ranging from 9 to 49 departments, 2 and 4 periods. The experimental results show that the proposed method is an alternative way for the plant layout designer to determine the layouts during multi-period planning horizon.

Keywords: Ant colony optimization, Dynamicprogramming, Dynamic facility layout planning, Metaheuristic

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2137 Aircraft Selection Using Preference Optimization Programming (POP)

Authors: C. Ardil

Abstract:

A multiple-criteria decision support system is proposed for the best aircraft selection decision. Various strategic, economic, environmental, and risk-related factors can directly or indirectly influence this choice, and they should be taken into account in the decision-making process. The paper suggests a multiple-criteria analysis to aid in the airline management's decision-making process when choosing an appropriate aircraft. In terms of the suggested approach, an integrated entropic preference optimization programming (POP) for fleet modeling risk analysis is applied. The findings of the study of multiple criteria analysis indicate that the A321(neo) aircraft type is the best alternative in this particular optimization instance. The proposed methodology can be applied to other complex engineering problems involving multiple criteria analysis.

Keywords: Aircraft selection, decision making, multiple criteria decision making, preference optimization programming, POP, entropic weight method, TOPSIS, WSM, WPM

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2136 Analysis of Self Excited Induction Generator using Particle Swarm Optimization

Authors: Hassan E. A. Ibrahim, Mohamed F. Serag

Abstract:

In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.

Keywords: Evolution theory, MATLAB, optimization, PSO, SEIG.

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2135 Establishing a Probabilistic Model of Extrapolated Wind Speed Data for Wind Energy Prediction

Authors: Mussa I. Mgwatu, Reuben R. M. Kainkwa

Abstract:

Wind is among the potential energy resources which can be harnessed to generate wind energy for conversion into electrical power. Due to the variability of wind speed with time and height, it becomes difficult to predict the generated wind energy more optimally. In this paper, an attempt is made to establish a probabilistic model fitting the wind speed data recorded at Makambako site in Tanzania. Wind speeds and direction were respectively measured using anemometer (type AN1) and wind Vane (type WD1) both supplied by Delta-T-Devices at a measurement height of 2 m. Wind speeds were then extrapolated for the height of 10 m using power law equation with an exponent of 0.47. Data were analysed using MINITAB statistical software to show the variability of wind speeds with time and height, and to determine the underlying probability model of the extrapolated wind speed data. The results show that wind speeds at Makambako site vary cyclically over time; and they conform to the Weibull probability distribution. From these results, Weibull probability density function can be used to predict the wind energy.

Keywords: Probabilistic models, wind speed, wind energy

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2134 Dynamic Clustering using Particle Swarm Optimization with Application in Unsupervised Image Classification

Authors: Mahamed G.H. Omran, Andries P Engelbrecht, Ayed Salman

Abstract:

A new dynamic clustering approach (DCPSO), based on Particle Swarm Optimization, is proposed. This approach is applied to unsupervised image classification. The proposed approach automatically determines the "optimum" number of clusters and simultaneously clusters the data set with minimal user interference. The algorithm starts by partitioning the data set into a relatively large number of clusters to reduce the effects of initial conditions. Using binary particle swarm optimization the "best" number of clusters is selected. The centers of the chosen clusters is then refined via the Kmeans clustering algorithm. The experiments conducted show that the proposed approach generally found the "optimum" number of clusters on the tested images.

Keywords: Clustering Validation, Particle Swarm Optimization, Unsupervised Clustering, Unsupervised Image Classification.

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2133 PI Control for Second Order Delay System with Tuning Parameter Optimization

Authors: R. Farkh, K. Laabidi, M. Ksouri

Abstract:

In this paper, we consider the control of time delay system by Proportional-Integral (PI) controller. By Using the Hermite- Biehler theorem, which is applicable to quasi-polynomials, we seek a stability region of the controller for first order delay systems. The essence of this work resides in the extension of this approach to second order delay system, in the determination of its stability region and the computation of the PI optimum parameters. We have used the genetic algorithms to lead the complexity of the optimization problem.

Keywords: Genetic algorithm, Hermit-Biehler theorem, optimization, PI controller, second order delay system, stability region.

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2132 Development of an Intelligent Tool for Planning the Operation

Authors: T. R. Alencar, P. T. Leite

Abstract:

Several optimization algorithms specifically applied to the problem of Operation Planning of Hydrothermal Power Systems have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. Thus, this paper presents the development of a computational tool for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique, Genetic Algorithms and programming language Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: Energy, Optimization, Hydrothermal Power Systemsand Genetic Algorithms

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