Search results for: Portfolio optimization
1721 Economic Load Dispatch with Daily Load Patterns and Generator Constraints by Particle Swarm Optimization
Authors: N. Phanthuna V. Phupha N. Rugthaicharoencheep, S. Lerdwanittip
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18461720 Optimal Portfolio Selection in a DC Pension with Multiple Contributors and the Impact of Stochastic Additional Voluntary Contribution on the Optimal Investment Strategy
Authors: Edikan E. Akpanibah, Okwigbedi Oghen’Oro
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In this paper, we studied the optimal portfolio selection in a defined contribution (DC) pension scheme with multiple contributors under constant elasticity of variance (CEV) model and the impact of stochastic additional voluntary contribution on the investment strategies. We assume that the voluntary contributions are stochastic and also consider investments in a risk free asset and a risky asset to increase the expected returns of the contributing members. We derived a stochastic differential equation which consists of the members’ monthly contributions and the invested fund and obtained an optimized problem with the help of Hamilton Jacobi Bellman equation. Furthermore, we find an explicit solution for the optimal investment strategy with stochastic voluntary contribution using power transformation and change of variables method and the corresponding optimal fund size was obtained. We discussed the impact of the voluntary contribution on the optimal investment strategy with numerical simulations and observed that the voluntary contribution reduces the optimal investment strategy of the risky asset.
Keywords: DC pension fund, Hamilton-Jacobi-Bellman, optimal investment strategies, power transformation method, stochastic, voluntary contribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8211719 Application of Heuristic Integration Ant Colony Optimization in Path Planning
Authors: Zeyu Zhang, Guisheng Yin, Ziying Zhang, Liguo Zhang
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This paper mainly studies the path planning method based on ant colony optimization (ACO), and proposes heuristic integration ant colony optimization (HIACO). This paper not only analyzes and optimizes the principle, but also simulates and analyzes the parameters related to the application of HIACO in path planning. Compared with the original algorithm, the improved algorithm optimizes probability formula, tabu table mechanism and updating mechanism, and introduces more reasonable heuristic factors. The optimized HIACO not only draws on the excellent ideas of the original algorithm, but also solves the problems of premature convergence, convergence to the sub optimal solution and improper exploration to some extent. HIACO can be used to achieve better simulation results and achieve the desired optimization. Combined with the probability formula and update formula, several parameters of HIACO are tested. This paper proves the principle of the HIACO and gives the best parameter range in the research of path planning.
Keywords: Ant colony optimization, heuristic integration, path planning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6561718 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42801717 Application of Legendre Transformation to Portfolio Optimization
Authors: Peter Benneth, Tsaroh N. Theophilus, Prince Benjamin
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This research work aims at studying the application of Legendre Transformation Method (LTM) to Hamilton Jacobi Bellman (HJB) equation which is an example of optimal control problem. We discuss the steps involved in modelling the HJB equation as it relates to mathematical finance by applying the Ito’s lemma and maximum principle theorem. By applying the LTM and dual theory, the resultant HJB equation is transformed to a linear Partial Differential Equation (PDE). Also, the Optimal Investment Strategy (OIS) and the optimal value function were obtained under the exponential utility function. Furthermore, some numerical results were also presented with observations that the OIS under exponential utility is directly proportional to the appreciation rate of the risky asset and inversely proportional to the instantaneous volatility, predetermined interest rate, risk averse coefficient. Finally, it was observed that the optimal fund size is an increasing function of the risk free interest rate. This result is consistent with some existing results.
Keywords: Legendre transformation method, Optimal investment strategy, Ito’s lemma, Hamilton Jacobi Bellman equation, Geometric Brownian motion, financial market.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 171716 Voltage Stability Enhancement Using Cat Swarm Optimization Algorithm
Authors: P. Suryakumari, P. Kantarao
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24231715 A Discrete Choice Modeling Approach to Modular Systems Design
Authors: Ivan C. Mustakerov, Daniela I. Borissova
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20111714 A Holistic Approach for Technical Product Optimization
Authors: H. Lang, M. Bader, A. Buchroithner
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26441713 Application of Adaptive Genetic Algorithm in Function Optimization
Authors: Panpan Xu, Shulin Sui
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The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.
Keywords: Genetic algorithm, Adaptive genetic algorithm, Function optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17091712 Optimal Design of UPFC Based Damping Controller Using Iteration PSO
Authors: Amin Safari, Hossein Shayeghi
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17961711 Optimization of Fuzzy Cluster Nodes in Cellular Multimedia Networks
Authors: J. D. Mallapur, Supriya H., Santosh B. K., Tej H.
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15611710 Building Gabor Filters from Retinal Responses
Authors: Johannes Partzsch, Christian Mayr, Rene Schuffny
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23921709 Combining Ant Colony Optimization and Dynamic Programming for Solving a Dynamic Facility Layout Problem
Authors: A. Udomsakdigool, S. Bangsaranthip
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19341708 Aircraft Selection Using Preference Optimization Programming (POP)
Authors: C. Ardil
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5991707 Analysis of Self Excited Induction Generator using Particle Swarm Optimization
Authors: Hassan E. A. Ibrahim, Mohamed F. Serag
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24531706 Dynamic Clustering using Particle Swarm Optimization with Application in Unsupervised Image Classification
Authors: Mahamed G.H. Omran, Andries P Engelbrecht, Ayed Salman
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24451705 PI Control for Second Order Delay System with Tuning Parameter Optimization
Authors: R. Farkh, K. Laabidi, M. Ksouri
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17671704 Development of an Intelligent Tool for Planning the Operation
Authors: T. R. Alencar, P. T. Leite
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16901703 Preliminary Study on Fixture Layout Optimization Using Element Strain Energy
Authors: Zeshan Ahmad, Matteo Zoppi, Rezia Molfino
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The objective of positioning the fixture elements in the fixture is to make the workpiece stiff, so that geometric errors in the manufacturing process can be reduced. Most of the work for optimal fixture layout used the minimization of the sum of the nodal deflection normal to the surface as objective function. All deflections in other direction have been neglected. We propose a new method for fixture layout optimization in this paper, which uses the element strain energy. The deformations in all the directions have been considered in this way. The objective function in this method is to minimize the sum of square of element strain energy. Strain energy and stiffness are inversely proportional to each other. The optimization problem is solved by the sequential quadratic programming method. Three different kinds of case studies are presented, and results are compared with the method using nodal deflections as objective function to verify the propose method.Keywords: Fixture layout, optimization, strain energy, quadratic programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15381702 A Comparison among Wolf Pack Search and Four other Optimization Algorithms
Authors: Shahla Shoghian, Maryam Kouzehgar
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The main objective of this paper is applying a comparison between the Wolf Pack Search (WPS) as a newly introduced intelligent algorithm with several other known algorithms including Particle Swarm Optimization (PSO), Shuffled Frog Leaping (SFL), Binary and Continues Genetic algorithms. All algorithms are applied on two benchmark cost functions. The aim is to identify the best algorithm in terms of more speed and accuracy in finding the solution, where speed is measured in terms of function evaluations. The simulation results show that the SFL algorithm with less function evaluations becomes first if the simulation time is important, while if accuracy is the significant issue, WPS and PSO would have a better performance.Keywords: Wolf Pack Search, Particle Swarm Optimization, Continues Genetic Algorithm, Binary Genetic Algorithm, Shuffled Frog Leaping, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37331701 A Contribution to 3D Modeling of Manufacturing Tolerance Optimization
Authors: F. Sebaa, A. Cheikh, M. Rahou
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The study of the generated defects on manufactured parts shows the difficulty to maintain parts in their positions during the machining process and to estimate them during the pre-process plan. This work presents a contribution to the development of 3D models for the optimization of the manufacturing tolerances. An experimental study allows the measurement of the defects of part positioning for the determination of ε and the choice of an optimal setup of the part. An approach of 3D tolerance based on the small displacements method permits the determination of the manufacturing errors upstream. A developed tool, allows an automatic generation of the tolerance intervals along the three axes.Keywords: Manufacturing tolerances, 3D modeling, optimization, errors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15611700 Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution
Authors: Tomoaki Hashimoto
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In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research fields. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method for unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with unknown probability distribution.Keywords: Optimal control, stochastic systems, discrete-time systems, probabilistic constraints.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19131699 Multimachine Power System Stabilizers Design Using PSO Algorithm
Authors: H. Shayeghi, A. Safari, H. A. Shayanfar
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In this paper, multiobjective design of multi-machine Power System Stabilizers (PSSs) using Particle Swarm Optimization (PSO) is presented. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electro-mechanical modes of all machines to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The PSSs parameters tuning problem is converted to an optimization problem which is solved by PSO with the eigenvalue-based multiobjective function. The proposed PSO based PSSs is tested on a multimachine power system under different operating conditions and disturbances through eigenvalue analysis and some performance indices to illustrate its robust performance.
Keywords: PSS Design, Particle Swarm Optimization, Dynamic Stability, Multiobjective Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26361698 Optimal Synthesis of Multipass Heat Exchanger without Resorting to Correction Factor
Authors: Bharat B. Gulyani, Anuj Jain, Shalendra Kumar
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Customarily, the LMTD correction factor, FT, is used to screen alternative designs for a heat exchanger. Designs with unacceptably low FT values are discarded. In this paper, authors have proposed a more fundamental criterion, based on feasibility of a multipass exchanger as the only criteria, followed by economic optimization. This criterion, coupled with asymptotic energy targets, provide the complete optimization space in a heat exchanger network (HEN), where cost-optimization of HEN can be performed with only Heat Recovery Approach temperature (HRAT) and number-of-shells as variables.Keywords: heat exchanger, heat exchanger networks, LMTD correction factor, shell targeting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43161697 Bi-Criteria Latency Optimization of Intra-and Inter-Autonomous System Traffic Engineering
Authors: K. Vidya, V.Rhymend Uthariaraj
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Traffic Engineering (TE) is the process of controlling how traffic flows through a network in order to facilitate efficient and reliable network operations while simultaneously optimizing network resource utilization and traffic performance. TE improves the management of data traffic within a network and provides the better utilization of network resources. Many research works considers intra and inter Traffic Engineering separately. But in reality one influences the other. Hence the effective network performances of both inter and intra Autonomous Systems (AS) are not optimized properly. To achieve a better Joint Optimization of both Intra and Inter AS TE, we propose a joint Optimization technique by considering intra-AS features during inter – AS TE and vice versa. This work considers the important criterion say latency within an AS and between ASes. and proposes a Bi-Criteria Latency optimization model. Hence an overall network performance can be improved by considering this jointoptimization technique in terms of Latency.Keywords: Inter-Domain Routing , Measurement, OptimizationPerformance, Traffic Engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15071696 A Probabilistic Optimization Approach for a Gas Processing Plant under Uncertain Feed Conditions and Product Requirements
Authors: G. Mesfin, M. Shuhaimi
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This paper proposes a new optimization techniques for the optimization a gas processing plant uncertain feed and product flows. The problem is first formulated using a continuous linear deterministic approach. Subsequently, the single and joint chance constraint models for steady state process with timedependent uncertainties have been developed. The solution approach is based on converting the probabilistic problems into their equivalent deterministic form and solved at different confidence levels Case study for a real plant operation has been used to effectively implement the proposed model. The optimization results indicate that prior decision has to be made for in-operating plant under uncertain feed and product flows by satisfying all the constraints at 95% confidence level for single chance constrained and 85% confidence level for joint chance constrained optimizations cases.Keywords: Butane, Feed composition, LPG, Productspecification, Propane.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13861695 Enhanced Particle Swarm Optimization Approach for Solving the Non-Convex Optimal Power Flow
Authors: M. R. AlRashidi, M. F. AlHajri, M. E. El-Hawary
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An enhanced particle swarm optimization algorithm (PSO) is presented in this work to solve the non-convex OPF problem that has both discrete and continuous optimization variables. The objective functions considered are the conventional quadratic function and the augmented quadratic function. The latter model presents non-differentiable and non-convex regions that challenge most gradient-based optimization algorithms. The optimization variables to be optimized are the generator real power outputs and voltage magnitudes, discrete transformer tap settings, and discrete reactive power injections due to capacitor banks. The set of equality constraints taken into account are the power flow equations while the inequality ones are the limits of the real and reactive power of the generators, voltage magnitude at each bus, transformer tap settings, and capacitor banks reactive power injections. The proposed algorithm combines PSO with Newton-Raphson algorithm to minimize the fuel cost function. The IEEE 30-bus system with six generating units is used to test the proposed algorithm. Several cases were investigated to test and validate the consistency of detecting optimal or near optimal solution for each objective. Results are compared to solutions obtained using sequential quadratic programming and Genetic Algorithms.Keywords: Particle Swarm Optimization, Optimal Power Flow, Economic Dispatch.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23571694 Aerodynamics and Optimization of Airfoil Under Ground Effect
Authors: Kyoungwoo Park, Byeong Sam Kim, Juhee Lee, Kwang Soo Kim
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The Prediction of aerodynamic characteristics and shape optimization of airfoil under the ground effect have been carried out by integration of computational fluid dynamics and the multiobjective Pareto-based genetic algorithm. The main flow characteristics around an airfoil of WIG craft are lift force, lift-to-drag ratio and static height stability (H.S). However, they show a strong trade-off phenomenon so that it is not easy to satisfy the design requirements simultaneously. This difficulty can be resolved by the optimal design. The above mentioned three characteristics are chosen as the objective functions and NACA0015 airfoil is considered as a baseline model in the present study. The profile of airfoil is constructed by Bezier curves with fourteen control points and these control points are adopted as the design variables. For multi-objective optimization problems, the optimal solutions are not unique but a set of non-dominated optima and they are called Pareto frontiers or Pareto sets. As the results of optimization, forty numbers of non- dominated Pareto optima can be obtained at thirty evolutions.Keywords: Aerodynamics, Shape optimization, Airfoil on WIGcraft, Genetic algorithm, Computational fluid dynamics (CFD).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32171693 Modeling and Optimization of Aggregate Production Planning - A Genetic Algorithm Approach
Authors: B. Fahimnia, L.H.S. Luong, R. M. Marian
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The Aggregate Production Plan (APP) is a schedule of the organization-s overall operations over a planning horizon to satisfy demand while minimizing costs. It is the baseline for any further planning and formulating the master production scheduling, resources, capacity and raw material planning. This paper presents a methodology to model the Aggregate Production Planning problem, which is combinatorial in nature, when optimized with Genetic Algorithms. This is done considering a multitude of constraints of contradictory nature and the optimization criterion – overall cost, made up of costs with production, work force, inventory, and subcontracting. A case study of substantial size, used to develop the model, is presented, along with the genetic operators.Keywords: Aggregate Production Planning, Costs, and Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25741692 A Bacterial Foraging Optimization Algorithm Applied to the Synthesis of Polyacrylamide Hydrogels
Authors: Florin Leon, Silvia Curteanu
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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.
Keywords: Bacterial foraging optimization, hydrogels, neural networks, modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 713