Search results for: Conic optimization
1807 Applications of Conic Optimization and Quadratic Programming in the Investigation of Index Arbitrage in the Thai Derivatives and Equity Markets
Authors: Satjaporn Tungsong, Gun Srijuntongsiri
Abstract:This research seeks to investigate the frequency and profitability of index arbitrage opportunities involving the SET50 futures, SET50 component stocks, and the ThaiDEX SET50 ETF (ticker symbol: TDEX). In particular, the frequency and profit of arbitrage are measured in the following three arbitrage tests: (1) SET50 futures vs. ThaiDEX SET50 ETF, (2) SET50 futures vs. SET50 component stocks, and (3) ThaiDEX SET50 ETF vs. SET50 component stocks are investigated. For tests (2) and (3), the problems involve conic optimization and quadratic programming as subproblems. This research is first to apply conic optimization and quadratic programming techniques in the context of index arbitrage and is first to investigate such index arbitrage in the Thai equity and derivatives markets. Thus, the contribution of this study is twofold. First, its results would help understand the contribution of the derivatives securities to the efficiency of the Thai markets. Second, the methodology employed in this study can be applied to other geographical markets, with minor adjustments.
Keywords: Conic optimization, Equity index arbitrage, Executionlags, Quadratic programming, SET50 index futures, ThaiDEX SET50ETF, Transaction costsProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1454
1806 Recovering the Clipped OFDM Figurebased on the Conic Function
Authors: Linjun Wu, Shihua Zhu, Xingle Feng
In Orthogonal Frequency Division Multiplexing (OFDM) systems, the peak to average power ratio (PAR) is much high. The clipping signal scheme is a useful method to reduce PAR. Clipping the OFDM signal, however, increases the overall noise level by introducing clipping noise. It is necessary to recover the figure of the original signal at receiver in order to reduce the clipping noise. Considering the continuity of the signal and the figure of the peak, we obtain a certain conic function curve to replace the clipped signal module within the clipping time. The results of simulation show that the proposed scheme can reduce the systems? BER (bit-error rate) 10 times when signal-to-interference-and noise-ratio (SINR) equals to 12dB. And the BER performance of the proposed scheme is superior to that of kim's scheme, too.
Keywords: Orthogonal Frequency Division Multiplexing, Peak-to-Average Power Ratio, clipping time, conic function.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1396
1805 Influence of Replacement Used Reference Coordinate System for Georeferencing of the Old Map of Europe
Authors: Jakub Havlicek, Jiri Cajthaml
Abstract:The article describes the effect of the replacement of the used reference coordinate system in the georeferencing of an old map of Europe. The map was georeferenced into three types of projection – the equal-area conic (original cartographic projection), cylindrical Plate Carrée and cylindrical Mercator map projection. The map was georeferenced by means of the affine and the second-order polynomial transformation. The resulting georeferenced raster datasets from the Plate Carrée and Mercator projection were projected into the equal-area conic projection by means of projection equations. The output is the comparison of drawn graphics, the magnitude of standard deviations for individual projections and types of transformation.
Keywords: Georeferencing, reference coordinate system, transformation, standard deviation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1327
1804 A Method of Planar-Template- Based Camera Self-Calibration for Single-View
Abstract:Camera calibration is an important step in 3D reconstruction. Camera calibration may be classified into two major types: traditional calibration and self-calibration. However, a calibration method in using a checkerboard is intermediate between traditional calibration and self-calibration. A self is proposed based on a square in this paper. Only a square in the planar template, the camera self-calibration can be completed through the single view. The proposed algorithm is that the virtual circle and straight line are established by a square on planar template, and circular points, vanishing points in straight lines and the relation between them are be used, in order to obtain the image of the absolute conic (IAC) and establish the camera intrinsic parameters. To make the calibration template is simpler, as compared with the Zhang Zhengyou-s method. Through real experiments and experiments, the experimental results show that this algorithm is feasible and available, and has a certain precision and robustness.
Keywords: Absolute conic, camera calibration, circle point, vanishing point.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1505
1803 A Short Reflection on the Strengths and Weaknesses of Simulation Optimization
Authors: P. Vazan, P. Tanuska
The paper provides the basic overview of simulation optimization. The procedure of its practical using is demonstrated on the real example in simulator Witness. The simulation optimization is presented as a good tool for solving many problems in real praxis especially in production systems. The authors also characterize their own experiences and they mention the strengths and weakness of simulation optimization.
Keywords: discrete event simulation, simulation optimization, WitnessProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2441
1802 Particle Swarm Optimization with Reduction for Global Optimization Problems
Authors: Michiharu Maeda, Shinya Tsuda
Abstract:This paper presents an algorithm of particle swarm optimization with reduction for global optimization problems. Particle swarm optimization is an algorithm which refers to the collective motion such as birds or fishes, and a multi-point search algorithm which finds a best solution using multiple particles. Particle swarm optimization is so flexible that it can adapt to a number of optimization problems. When an objective function has a lot of local minimums complicatedly, the particle may fall into a local minimum. For avoiding the local minimum, a number of particles are initially prepared and their positions are updated by particle swarm optimization. Particles sequentially reduce to reach a predetermined number of them grounded in evaluation value and particle swarm optimization continues until the termination condition is met. In order to show the effectiveness of the proposed algorithm, we examine the minimum by using test functions compared to existing algorithms. Furthermore the influence of best value on the initial number of particles for our algorithm is discussed.
Keywords: Particle swarm optimization, Global optimization, Metaheuristics, Reduction.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1479
1801 Simulated Annealing Application for Structural Optimization
Authors: Farhad Kolahan, M. Hossein Abolbashari, Samaeddin Mohitzadeh
Abstract:Several methods are available for weight and shape optimization of structures, among which Evolutionary Structural Optimization (ESO) is one of the most widely used methods. In ESO, however, the optimization criterion is completely case-dependent. Moreover, only the improving solutions are accepted during the search. In this paper a Simulated Annealing (SA) algorithm is used for structural optimization problem. This algorithm differs from other random search methods by accepting non-improving solutions. The implementation of SA algorithm is done through reducing the number of finite element analyses (function evaluations). Computational results show that SA can efficiently and effectively solve such optimization problems within short search time.
Keywords: Simulated annealing, Structural optimization, Compliance, C.V. product.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1824
1800 Reliability-Based Topology Optimization Based on Evolutionary Structural Optimization
Authors: Sang-Rak Kim, Jea-Yong Park, Won-Goo Lee, Jin-Shik Yu, Seog-Young Han
Abstract:This paper presents a Reliability-Based Topology Optimization (RBTO) based on Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of the uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.
Keywords: Evolutionary Structural Optimization, PerformanceMeasure Approach, Reliability-Based Topology Optimization, Reliability Index Approach.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2610
1799 A Mean–Variance–Skewness Portfolio Optimization Model
Authors: Kostas Metaxiotis
Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.
Keywords: Evolutionary algorithms, portfolio optimization, skewness, stock selection.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1103
1798 Non-Stationary Stochastic Optimization of an Oscillating Water Column
Authors: María L. Jalón, Feargal Brennan
Abstract:A non-stationary stochastic optimization methodology is applied to an OWC (oscillating water column) to find the design that maximizes the wave energy extraction. Different temporal cycles are considered to represent the long-term variability of the wave climate at the site in the optimization problem. The results of the non-stationary stochastic optimization problem are compared against those obtained by a stationary stochastic optimization problem. The comparative analysis reveals that the proposed non-stationary optimization provides designs with a better fit to reality. However, the stationarity assumption can be adequate when looking at averaged system response.
Keywords: Non-stationary stochastic optimization, oscillating water column, temporal variability, wave energy.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 698
1797 Contribution to the Query Optimization in the Object-Oriented Databases
Authors: Minyar Sassi, Amel Grissa-Touzi
Abstract:Appeared toward 1986, the object-oriented databases management systems had not known successes knew five years after their birth. One of the major difficulties is the query optimization. We propose in this paper a new approach that permits to enrich techniques of query optimization existing in the object-oriented databases. Seen success that knew the query optimization in the relational model, our approach inspires itself of these optimization techniques and enriched it so that they can support the new concepts introduced by the object databases.
Keywords: Query, query optimization, relational databases, object-oriented databases.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1412
1796 Evaluating and Selecting Optimization Software Packages: A Framework for Business Applications
Authors: Waleed Abohamad, Amr Arisha
Abstract:Owing the fact that optimization of business process is a crucial requirement to navigate, survive and even thrive in today-s volatile business environment, this paper presents a framework for selecting a best-fit optimization package for solving complex business problems. Complexity level of the problem and/or using incorrect optimization software can lead to biased solutions of the optimization problem. Accordingly, the proposed framework identifies a number of relevant factors (e.g. decision variables, objective functions, and modeling approach) to be considered during the evaluation and selection process. Application domain, problem specifications, and available accredited optimization approaches are also to be regarded. A recommendation of one or two optimization software is the output of the framework which is believed to provide the best results of the underlying problem. In addition to a set of guidelines and recommendations on how managers can conduct an effective optimization exercise is discussed.
Keywords: Complex Business Problems, Optimization, Selection Criteria, Software Evaluation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2804
1795 Two-Stage Approach for Solving the Multi-Objective Optimization Problem on Combinatorial Configurations
Authors: Liudmyla Koliechkina, Olena Dvirna
Abstract:The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps.
Keywords: Discrete set, linear combinatorial optimization, multi-objective optimization, multipermutation, Pareto solutions, partial permutation set, permutation, structural graph.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 505
1794 Application of Soft Computing Methods for Economic Dispatch in Power Systems
Authors: Jagabondhu Hazra, Avinash Sinha
Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Keywords: Ant colony optimization, bacteria foraging optimization, economic dispatch, evolutionary algorithm, genetic algorithm, particle swarm optimization.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2362
1793 Model of Optimal Centroids Approach for Multivariate Data Classification
Authors: Pham Van Nha, Le Cam Binh
Abstract:Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.
Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 666
1792 Dynamic Mesh Based Airfoil Design Optimization
Authors: Zhu Xiong-feng, Hou Zhong-xi, Guo Zheng, Liu Zhao-Wei
A method of dynamic mesh based airfoil optimization is proposed according to the drawbacks of surrogate model based airfoil optimization. Programs are designed to achieve the dynamic mesh. Boundary condition is add by integrating commercial software Pointwise, meanwhile the CFD calculation is carried out by commercial software Fluent. The data exchange and communication between the software and programs referred above have been accomplished, and the whole optimization process is performed in iSIGHT platform. A simplified airfoil optimization study case is brought out to show that aerodynamic performances of airfoil have been significantly improved, even save massive repeat operations and increase the robustness and credibility of the optimization result. The case above proclaims that dynamic mesh based airfoil optimization is an effective and high efficient method.
Keywords: unmanned air vehicles, dynamic mesh, airfoil optimization, CFD, genetic algorithmProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3252
1791 Query Optimization Techniques for XML Databases
Authors: Su Cheng Haw, G. S. V. Radha Krishna Rao
Abstract:Over the past few years, XML (eXtensible Mark-up Language) has emerged as the standard for information representation and data exchange over the Internet. This paper provides a kick-start for new researches venturing in XML databases field. We survey the storage representation for XML document, review the XML query processing and optimization techniques with respect to the particular storage instance. Various optimization technologies have been developed to solve the query retrieval and updating problems. Towards the later year, most researchers proposed hybrid optimization techniques. Hybrid system opens the possibility of covering each technology-s weakness by its strengths. This paper reviews the advantages and limitations of optimization techniques.
Keywords: indexing, labeling scheme, query optimization, XML storage.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1833
1790 IBFO_PSO: Evaluating the Performance of Bio-Inspired Integrated Bacterial Foraging Optimization Algorithm and Particle Swarm Optimization Algorithm in MANET Routing
Authors: K. Geetha, P. Thangaraj, C. Rasi Priya, C. Rajan, S. Geetha
Abstract:This paper presents the performance of Integrated Bacterial Foraging Optimization and Particle Swarm Optimization (IBFO_PSO) technique in MANET routing. The BFO is a bio-inspired algorithm, which simulates the foraging behavior of bacteria. It is effectively applied in improving the routing performance in MANET. In results, it is proved that the PSO integrated with BFO reduces routing delay, energy consumption and communication overhead.
Keywords: Ant Colony Optimization, Bacterial Foraging Optimization, Hybrid Routing Intelligent Algorithm, Naturally inspired algorithms, Particle Swarm Optimization.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2611
1789 A Novel Design Approach for Mechatronic Systems Based On Multidisciplinary Design Optimization
Authors: Didier Casner, Jean Renaud, Remy Houssin, Dominique Knittel
In this paper, a novel approach for the multidisciplinary design optimization (MDO) of complex mechatronic systems. This approach, which is a part of a global project aiming to include the MDO aspect inside an innovative design process. As a first step, the paper considers the MDO as a redesign approach which is limited to the parametric optimization. After defining and introducing the different keywords, the proposed method which is based on the V-Model which is commonly used in mechatronics.
Keywords: mechatronics, Multidisciplinary Design Optimization (MDO), multiobjective optimization, engineering design.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1895
1788 An Optimization of Orbital Transfer for Spacecrafts with Finite-thrust Based on Legendre Pseudospectral Method
Authors: Yanan Yang, Zhigang Wang, Xiang Chen
Abstract:This paper presents the use of Legendre pseudospectral method for the optimization of finite-thrust orbital transfer for spacecrafts. In order to get an accurate solution, the System-s dynamics equations were normalized through a dimensionless method. The Legendre pseudospectral method is based on interpolating functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This is used to transform the optimal control problem into a constrained parameter optimization problem. The developed novel optimization algorithm can be used to solve similar optimization problems of spacecraft finite-thrust orbital transfer. The results of a numerical simulation verified the validity of the proposed optimization method. The simulation results reveal that pseudospectral optimization method is a promising method for real-time trajectory optimization and provides good accuracy and fast convergence.
Keywords: Finite-thrust, Orbital transfer, Legendre pseudospectral methodProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1684
1787 Transmission Lines Loading Enhancement Using ADPSO Approach
Authors: M. Mahdavi, H. Monsef, A. Bagheri
Abstract:Discrete particle swarm optimization (DPSO) is a powerful stochastic evolutionary algorithm that is used to solve the large-scale, discrete and nonlinear optimization problems. However, it has been observed that standard DPSO algorithm has premature convergence when solving a complex optimization problem like transmission expansion planning (TEP). To resolve this problem an advanced discrete particle swarm optimization (ADPSO) is proposed in this paper. The simulation result shows that optimization of lines loading in transmission expansion planning with ADPSO is better than DPSO from precision view point.
Keywords: ADPSO, TEP problem, Lines loading optimization.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1472
1786 Mathematical Programming Models for Portfolio Optimization Problem: A Review
Authors: M. Mokhtar, A. Shuib, D. Mohamad
Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.
Keywords: Portfolio optimization, Mathematical programming, Multi-objective programming, Solution approaches.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6425
1785 Particle Swarm Optimization for Design of Water Distribution Systems
Authors: A. Vasan
Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.
Keywords: Water distribution systems, Optimization, Particle swarm optimization, Swarm intelligence, New York water supply system.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385
1784 The Whale Optimization Algorithm and Its Implementation in MATLAB
Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh
Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.
Keywords: Optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, Implementation, MATLAB.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2666
1783 Topology Optimization of Aircraft Fuselage Structure
Authors: Muniyasamy Kalanchiam, Baskar Mannai
Abstract:Topology Optimization is a defined as the method of determining optimal distribution of material for the assumed design space with functionality, loads and boundary conditions . Topology optimization can be used to optimize shape for the purposes of weight reduction, minimizing material requirements or selecting cost effective materials . Topology optimization has been implemented through the use of finite element methods for the analysis, and optimization techniques based on the method of moving asymptotes, genetic algorithms, optimality criteria method, level sets and topological derivatives. Case study of Typical “Fuselage design" is considered for this paper to explain the benefits of Topology Optimization in the design cycle. A cylindrical shell is assumed as the design space and aerospace standard pay loads were applied on the fuselage with wing attachments as constraints. Then topological optimization is done using Finite Element (FE) based software. This optimization results in the structural concept design which satisfies all the design constraints using minimum material.
Keywords: Fuselage, Topology optimization, payloads, designoptimization, Finite Element Analysis.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3933
1782 Big Bang – Big Crunch Optimization Method in Optimum Design of Complex Composite Laminates
Authors: Pavel Y. Tabakov
Abstract:An accurate optimal design of laminated composite structures may present considerable difficulties due to the complexity and multi-modality of the functional design space. The Big Bang – Big Crunch (BB-BC) optimization method is a relatively new technique and has already proved to be a valuable tool for structural optimization. In the present study the exceptional efficiency of the method is demonstrated by an example of the lay-up optimization of multilayered anisotropic cylinders based on a three-dimensional elasticity solution. It is shown that, due to its simplicity and speed, the BB-BC is much more efficient for this class of problems when compared to the genetic algorithms.
Keywords: Big Bang – Big Crunch method, optimization, composite laminates, pressure vessel.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2152
1781 Using Pattern Search Methods for Minimizing Clustering Problems
Authors: Parvaneh Shabanzadeh, Malik Hj Abu Hassan, Leong Wah June, Maryam Mohagheghtabar
Abstract:Clustering is one of an interesting data mining topics that can be applied in many fields. Recently, the problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the cluster analysis problem based on nonsmooth optimization techniques is developed. This optimization problem has a number of characteristics that make it challenging: it has many local minimum, the optimization variables can be either continuous or categorical, and there are no exact analytical derivatives. In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. These methods do not explicitly use derivatives, an important feature that has not been addressed in previous studies. Results of numerical experiments are presented which demonstrate the effectiveness of the proposed method.
Keywords: Clustering functions, Non-smooth Optimization, Nonconvex Optimization, Pattern Search Method.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1502
1780 Approximate Solution of Nonlinear Fredholm Integral Equations of the First Kind via Converting to Optimization Problems
Authors: Akbar H. Borzabadi, Omid S. Fard
Abstract:In this paper we introduce an approach via optimization methods to find approximate solutions for nonlinear Fredholm integral equations of the first kind. To this purpose, we consider two stages of approximation. First we convert the integral equation to a moment problem and then we modify the new problem to two classes of optimization problems, non-constraint optimization problems and optimal control problems. Finally numerical examples is proposed.
Keywords: Fredholm integral equation, Optimization method, Optimal control, Nonlinear and linear programmingProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1608
1779 Periodic Topology and Size Optimization Design of Tower Crane Boom
Authors: Wu Qinglong, Zhou Qicai, Xiong Xiaolei, Zhang Richeng
In order to achieve the layout and size optimization of the web members of tower crane boom, a truss topology and cross section size optimization method based on continuum is proposed considering three typical working conditions. Firstly, the optimization model is established by replacing web members with web plates. And the web plates are divided into several sub-domains so that periodic soft kill option (SKO) method can be carried out for topology optimization of the slender boom. After getting the optimized topology of web plates, the optimized layout of web members is formed through extracting the principal stress distribution. Finally, using the web member radius as design variable, the boom compliance as objective and the material volume of the boom as constraint, the cross section size optimization mathematical model is established. The size optimization criterion is deduced from the mathematical model by Lagrange multiplier method and Kuhn-Tucker condition. By comparing the original boom with the optimal boom, it is identified that this optimization method can effectively lighten the boom and improve its performance.
Keywords: Tower crane boom, topology optimization, size optimization, periodic, soft kill option, optimization criterion.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1108
1778 Ant Colony Optimization for Feature Subset Selection
Authors: Ahmed Al-Ani
Abstract:The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.
Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3007