Search results for: partial swarm optimisation
770 Intrusion Detection Using a New Particle Swarm Method and Support Vector Machines
Authors: Essam Al Daoud
Abstract:Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-kernel support vector machines. Particle swarm optimisation is used for feature selection by applying a new formula to update the position and the velocity of a particle; the support vector machine is used as a classifier. The proposed model is tested and compared with the other methods using the KDD CUP 1999 dataset. The results indicate that this new method achieves better accuracy rates than previous methods.
Keywords: Feature selection, Intrusion detection, Support vector machine, Particle swarm.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1833
769 Effect of Dry Cutting on Force and Tool Life When Machining Aerospace Material
Authors: K.Kadirgama, M.M.Noor, K.A. Abou-El-Hossein, H.H.Habeeb, M.M. Rahman, B.Mohamad, R.A. Bakar
Abstract:Cutting fluids, usually in the form of a liquid, are applied to the chip formation zone in order to improve the cutting conditions. Cutting fluid can be expensive and represents a biological and environmental hazard that requires proper recycling and disposal, thus adding to the cost of the machining operation. For these reasons dry cutting or dry machining has become an increasingly important approach; in dry machining no coolant or lubricant is used. This paper discussed the effect of the dry cutting on cutting force and tool life when machining aerospace materials (Haynes 242) with using two different coated carbide cutting tools (TiAlN and TiN/MT-TiCN/TiN). Response surface method (RSM) was used to minimize the number of experiments. ParTiAlN Swarm Optimisation (PSO) models were developed to optimize the machining parameters (cutting speed, federate and axial depth) and obtain the optimum cutting force and tool life. It observed that carbide cutting tool coated with TiAlN performed better in dry cutting compared with TiN/MT-TiCN/TiN. On other hand, TiAlN performed more superior with using of 100 % water soluble coolant. Due to the high temperature produced by aerospace materials, the cutting tool still required lubricant to sustain the heat transfer from the workpiece.
Keywords: Dry cutting, partial swarm optimisation, response surface method, tool lifeProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2354
768 DPSO Based SEPIC Converter in PV System under Partial Shading Condition
Authors: K. Divya, G. Sugumaran
This paper proposes an improved Maximum Power Point Tracking of PhotoVoltaic system using Deterministic Partical Swarm Optimization technique. This method has the ability to track the maximum power under varying environmental conditions i.e. partial shading conditions. The advantage of this method, particles moves in the restricted value of velocity to achieve the maximum power. SEPIC converter is employed to boost up the voltage of PV system. To estimate the value of the proposed method, MATLAB simulation carried out under partial shading condition.
Keywords: DPSO, Partial shading condition, P&O, PV, SEPIC.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2154
767 Selection of an Optimum Configuration of Solar PV Array under Partial Shaded Condition Using Particle Swarm Optimization
Authors: R. Ramaprabha
This paper presents an extraction of maximum energy from Solar Photovoltaic Array (SPVA) under partial shaded conditions by optimum selection of array size using Particle Swarm Optimization (PSO) technique. In this paper a detailed study on the output reduction of different SPVA configurations under partial shaded conditions have been carried out. A generalized MATLAB M-code based software model has been used for any required array size, configuration, shading patterns and number of bypass diodes. Comparative study has been carried out on different configurations by testing several shading scenarios. While the number of shading patterns and the rate of change are very low for stationary SPVA but these may be quite large for SPVA mounted on a mobile platforms. This paper presents the suitability of PSO technique to select optimum configuration for mobile arrays by calculating the global peak (GP) of different configurations and to transfer maximum power to the load.
Keywords: Global peak, Mobile PV arrays, Partial shading, optimization, PSO.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4083
766 Intelligent Swarm-Finding in Formation Control of Multi-Robots to Track a Moving Target
Authors: Anh Duc Dang, Joachim Horn
This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbors are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.
Keywords: Formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1978
765 Multiple Peaks Tracking Algorithm using Particle Swarm Optimization Incorporated with Artificial Neural Network
Authors: Mei Shan Ngan, Chee Wei Tan
Abstract:Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.
Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3624
764 A Cohesive Lagrangian Swarm and Its Application to Multiple Unicycle-like Vehicles
Authors: Jito Vanualailai, Bibhya Sharma
Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.
Keywords: Attractive-repulsive swarm model, individual-based swarm model, Lagrangian swarm model, Lyapunov stability, Lyapunov-like function, practical stability, unicycle.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1404
763 Towards Self-ware via Swarm-Array Computing
Authors: Blesson Varghese, Gerard McKee
Abstract:The work reported in this paper proposes Swarm-Array computing, a novel technique inspired by swarm robotics, and built on the foundations of autonomic and parallel computing. The approach aims to apply autonomic computing constructs to parallel computing systems and in effect achieve the self-ware objectives that describe self-managing systems. The constitution of swarm-array computing comprising four constituents, namely the computing system, the problem/task, the swarm and the landscape is considered. Approaches that bind these constituents together are proposed. Space applications employing FPGAs are identified as a potential area for applying swarm-array computing for building reliable systems. The feasibility of a proposed approach is validated on the SeSAm multi-agent simulator and landscapes are generated using the MATLAB toolkit.
Keywords: Swarm-Array computing, Autonomic computing, landscapes.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1481
762 Particle Swarm Optimisation of a Terminal Synergetic Controllers for a DC-DC Converter
Authors: H. Abderrezek, M. N. Harmas
DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DC-DC converters control mostly with asymptotic convergence. Synergetic control (SC) is a proven robust control approach and will be used here in a so called terminal scheme to achieve finite time convergence. Lyapounov synthesis is adopted to assure controlled system stability. Furthermore particle swarm optimization (PSO) algorithm, based on an integral time absolute of error (ITAE) criterion will be used to optimize controller parameters. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to classic synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed control method.
Keywords: DC-DC converter, PSO, finite time, terminal, synergetic control.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2099
761 Optimisation of a Dragonfly-Inspired Flapping Wing-Actuation System
Authors: Jia-Ming Kok, Javaan Chahl
An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.
Keywords: Flapping wing, Optimisation, Quasi-steady model.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2303
760 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 1476
759 Particle Swarm Optimization Based Interconnected Hydro-Thermal AGC System Considering GRC and TCPS
Authors: Banaja Mohanty, Prakash Kumar Hota
This paper represents performance of particle swarm optimisation (PSO) algorithm based integral (I) controller and proportional-integral controller (PI) for interconnected hydro-thermal automatic generation control (AGC) with generation rate constraint (GRC) and Thyristor controlled phase shifter (TCPS) in series with tie line. The control strategy of TCPS provides active control of system frequency. Conventional objective function integral square error (ISE) and another objective function considering square of derivative of change in frequencies of both areas and change in tie line power are considered. The aim of designing the objective function is to suppress oscillation in frequency deviations and change in tie line power oscillation. The controller parameters are searched by PSO algorithm by minimising the objective functions. The dynamic performance of the controllers I and PI, for both the objective functions, are compared with conventionally optimized I controller.
Keywords: Automatic generation control (AGC), Generation rate constraint (GRC), Thyristor control phase shifter (TCPS), Particle swarm optimization (PSO).Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1992
758 Particle Swarm Optimization with Interval-valued Genotypes and Its Application to Neuroevolution
Authors: Hidehiko Okada
The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.
Keywords: Evolutionary algorithms, swarm intelligence, particle swarm optimization, neural network, interval arithmetic.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1680
757 Canonical PSO based Nanorobot Control for Blood Vessel Repair
Authors: Pinfa Boonrong, Boonserm Kaewkamnerdpong
As nanotechnology advances, the use of nanotechnology for medical purposes in the field of nanomedicine seems more promising; the rise of nanorobots for medical diagnostics and treatments could be arriving in the near future. This study proposes a swarm intelligence based control mechanism for swarm nanorobots that operate as artificial platelets to search for wounds. The canonical particle swarm optimization algorithm is employed in this study. A simulation in the circulatory system is constructed and used for demonstrating the movement of nanorobots with essential characteristics to examine the performance of proposed control mechanism. The effects of three nanorobot capabilities including their perception range, maximum velocity and respond time are investigated. The results show that canonical particle swarm optimization can be used to control the early version nanorobots with simple behaviors and actions.
Keywords: Artificial platelets, canonical particle swarm optimization, nanomedicine, nanorobot, swarm intelligence.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2511
756 Comparative Dynamic Performance of Load Frequency Control of Nonlinear Interconnected Hydro-Thermal System Using Intelligent Techniques
Authors: Banaja Mohanty, Prakash Kumar Hota
Abstract:This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.
Keywords: Automatic generation control, governor dead band, generation rate constraint, differential evolution.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 931
755 Swarm Navigation in a Complex Environment
Authors: Jai Raj, Jito Vanualailai, Bibhya Sharma, Shonal Singh
Abstract:This paper proposes a solution to the motion planning and control problem of car-like mobile robots which is required to move safely to a designated target in a priori known workspace cluttered with swarm of boids exhibiting collective emergent behaviors. A generalized algorithm for target convergence and swarm avoidance is proposed that will work for any number of swarms. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws are demonstrated via computer simulations of an emergent behavior.
Keywords: Swarm, practical stability, motion planning, emergent.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1275
754 Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems
Authors: M. Senthil Arumugam, M.V.C. Rao
This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.
Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1785
753 Applying Autonomic Computing Concepts to Parallel Computing using Intelligent Agents
Authors: Blesson Varghese, Gerard T. McKee
The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores , a swarm-array computing approach, this paper focuses on 'Intelligent agents' another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.
Keywords: Autonomic computing, intelligent agents, swarm-array computing.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1464
752 Improvement of Gregory's formula using Particle Swarm Optimization
Authors: N. Khelil. L. Djerou , A. Zerarka, M. Batouche
Abstract:Consider the Gregory integration (G) formula with end corrections where h Δ is the forward difference operator with step size h. In this study we prove that can be optimized by minimizing some of the coefficient k a in the remainder term by particle swarm optimization. Experimental tests prove that can be rendered a powerful formula for library use.
Keywords: Numerical integration, Gregory Formula, Particle Swarm optimization.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1268
751 Cost Based Warranty Optimisation Using Genetic Algorithm
Authors: Dragan D. Stamenkovic, Vladimir M. Popovic
Abstract:Warranty is a powerful marketing tool for the manufacturer and a good protection for both the manufacturer and the customer. However, warranty always involves additional costs to the manufacturer, which depend on product reliability characteristics and warranty parameters. This paper presents an approach to optimisation of warranty parameters for known product failure distribution to reduce the warranty costs to the manufacturer while retaining the promotional function of the warranty. Combination free replacement and pro-rata warranty policy is chosen as a model and the length of free replacement period and pro-rata policy period are varied, as well as the coefficients that define the pro-rata cost function. Multiparametric warranty optimisation is done by using genetic algorithm. Obtained results are guideline for the manufacturer to choose the warranty policy that minimises the costs and maximises the profit.
Keywords: costs, genetic algorithm, optimisation, warranty.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1590
750 Obstacle and Collision Avoidance Control Laws of a Swarm of Boids
Authors: Bibhya Sharma, Jito Vanualailai, Jai Raj
This paper proposes a new obstacle and collision avoidance control laws for a three-dimensional swarm of boids. The swarm exhibit collective emergent behaviors whilst avoiding the obstacles in the workspace. While ﬂocking, animals group up in order to do various tasks and even a greater chance of evading predators. A generalized algorithms for attraction to the centroid, inter-individual swarm avoidance and obstacle avoidance is designed in this paper. We present a set of new continuous time-invariant velocity control laws is presented which is formulated via the Lyapunov-based control scheme. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws is demonstrated via computer simulations
Keywords: Lyapunov-based Control Scheme, Motion planning, Practical stability, Swarm.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2380
749 Half-Circle Fuzzy Number Threshold Determination via Swarm Intelligence Method
Authors: P.-W. Tsai, J.-W. Chen, C.-W. Chen, C.-Y. Chen
In recent years, many researchers are involved in the field of fuzzy theory. However, there are still a lot of issues to be resolved. Especially on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. Besides fuzzy theory, algorithms in swarm intelligence are also a popular field for the researchers. In this paper, a concept of utilizing one of the swarm intelligence method, which is called Bacterial-GA Foraging, to find the stabilized common P matrix for the fuzzy controller system is proposed. An example is given in in the paper, as well.
Keywords: Half-circle fuzzy numbers, predictions, swarm intelligence, Lyapunov method.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1618
748 Particle Swarm Optimization and Quantum Particle Swarm Optimization to Multidimensional Function Approximation
Authors: Diogo Silva, Fadul Rodor, Carlos Moraes
Abstract:This work compares the results of multidimensional function approximation using two algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum Particle Swarm Optimization (QPSO). These algorithms were both tested on three functions - The Rosenbrock, the Rastrigin, and the sphere functions - with different characteristics by increasing their number of dimensions. As a result, this study shows that the higher the function space, i.e. the larger the function dimension, the more evident the advantages of using the QPSO method compared to the PSO method in terms of performance and number of necessary iterations to reach the stop criterion.
Keywords: PSO, QPSO, function approximation, AI, optimization, multidimensional functions.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 669
747 Singular Value Decomposition Based Optimisation of Design Parameters of a Gearbox
Authors: Mehmet Bozca
Abstract:Singular value decomposition based optimisation of geometric design parameters of a 5-speed gearbox is studied. During the optimisation, a four-degree-of freedom torsional vibration model of the pinion gear-wheel gear system is obtained and the minimum singular value of the transfer matrix is considered as the objective functions. The computational cost of the associated singular value problems is quite low for the objective function, because it is only necessary to compute the largest and smallest singular values (μmax and μmin) that can be achieved by using selective eigenvalue solvers; the other singular values are not needed. The design parameters are optimised under several constraints that include bending stress, contact stress and constant distance between gear centres. Thus, by optimising the geometric parameters of the gearbox such as, the module, number of teeth and face width it is possible to obtain a light-weight-gearbox structure. It is concluded that the all optimised geometric design parameters also satisfy all constraints.
Keywords: Singular value, optimisation, gearbox, torsional vibration.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1535
746 Solving the Set Covering Problem Using the Binary Cat Swarm Optimization Metaheuristic
Authors: Broderick Crawford, Ricardo Soto, Natalia Berrios, Eduardo Olguin
Abstract:In this paper, we present a binary cat swarm optimization for solving the Set covering problem. The set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behavior of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. We illustrate this approach with 65 instances of the problem from the OR-Library. Moreover, we solve this problem with 40 new binarization techniques and we select the technical with the best results obtained. Finally, we make a comparison between results obtained in previous studies and the new binarization technique, that is, with roulette wheel as transfer function and V3 as discretization technique.
Keywords: Binary cat swarm optimization, set covering problem, metaheuristic, binarization methods.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1854
745 Solving the Economic Dispatch Problem using Novel Particle Swarm Optimization
Authors: S. Khamsawang, S. Jiriwibhakorn
Abstract:This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called particle swarm optimization with mutation operators (PSOM). The mutation operators are activated if velocity values of PSO nearly to zero or violated from the boundaries. Four scenarios of mutation operators are implemented for PSOM. The simulation results of all scenarios of the PSOM outperform over the PSO and other existing approaches which appeared in literatures.
Keywords: Novel particle swarm optimization, Economic dispatch problem, Mutation operator, Prohibited operating zones, Differential Evolution.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2168
744 The Particle Swarm Optimization Against the Runge’s Phenomenon: Application to the Generalized Integral Quadrature Method
Authors: A. Zerarka, A. Soukeur, N. Khelil
In the present work, we introduce the particle swarm optimization called (PSO in short) to avoid the Runge-s phenomenon occurring in many numerical problems. This new approach is tested with some numerical examples including the generalized integral quadrature method in order to solve the Volterra-s integral equations
Keywords: Integral equation, particle swarm optimization, Runge's phenomenon.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1291
743 Induction Motor Design with Limited Harmonic Currents Using Particle Swarm Optimization
Authors: C. Thanga Raj, S. P. Srivastava, Pramod Agarwal
This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
Keywords: Design, harmonics, induction motor, particle swarm optimizationProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1661
742 Spread Spectrum Code Estimationby Particle Swarm Algorithm
Authors: Vahid R. Asghari, Mehrdad Ardebilipour
Abstract:In the context of spectrum surveillance, a new method to recover the code of spread spectrum signal is presented, while the receiver has no knowledge of the transmitter-s spreading sequence. In our previous paper, we used Genetic algorithm (GA), to recover spreading code. Although genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems, but nonetheless, by increasing the length of the code, we will often lead to an unacceptable slow convergence speed. To solve this problem we introduce Particle Swarm Optimization (PSO) into code estimation in spread spectrum communication system. In searching process for code estimation, the PSO algorithm has the merits of rapid convergence to the global optimum, without being trapped in local suboptimum, and good robustness to noise. In this paper we describe how to implement PSO as a component of a searching algorithm in code estimation. Swarm intelligence boasts a number of advantages due to the use of mobile agents. Some of them are: Scalability, Fault tolerance, Adaptation, Speed, Modularity, Autonomy, and Parallelism. These properties make swarm intelligence very attractive for spread spectrum code estimation. They also make swarm intelligence suitable for a variety of other kinds of channels. Our results compare between swarm-based algorithms and Genetic algorithms, and also show PSO algorithm performance in code estimation process.
Keywords: Code estimation, Particle Swarm Optimization(PSO), Spread spectrum.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1988
741 Optimisation of Structural Design by Integrating Genetic Algorithms in the Building Information Modelling Environment
Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg
Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.
Keywords: Building Information Modelling, BIM, Genetic Algorithm, GA, architecture-engineering-construction, AEC, Optimisation, structure, design, population, generation, selection, mutation, crossover, offspring.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 666