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Power Demand Forecast Using Least-Squares Support Vector Machines

Power Demand Forecast Using Least-Squares Support Vector Mac...

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International Conference on Intelligent systems Applications to Power systems (ISAP)

作者： Leandro dos Santos Coelho Carlos Eduardo Klein Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil

This paper aims to share the results on forecasting power demand using least-squares support vector machines. The development is based on model estimation taking in consideration the past measurements for power demand and ambient temperature. All approximated models were evaluated using the multiple correlation coefficient (R 2 ) or mean absolute percentage error (MAPE) and maximum error combined as quality parameters.

关键词： Power demand Demand forecasting Support vector machines Power system modeling Temperature Power generation Power engineering and energy systems engineering and theory Power measurement System identification

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A Harmony search algorithm combined with differential operator applied to reliability-redundancy optimization

A Harmony search algorithm combined with differential operat...

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2009 IEEE International Conference on systems, Man and Cybernetics, SMC 2009

作者： Dos Santos Coelho, Leandro De Andrade Bernert, Diego Luis Mariani, Viviana Cocco Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)9781424427949

The reliability-redundancy allocation problem can be approached as a mixed-integer programming problem. It has been solved by using optimization techniques such as dynamic programming, integer programming, and mixed-integer nonlinear programming. On the other hand, a broad class of meta-heuristics has been developed for reliability-redundancy optimization. Recently, a new meta-heuristics called harmony search (HS) algorithm has emerged. HS was conceptualized using an analogy with music improvisation process where music players improvise the pitches of their instruments to obtain better harmony. This paper introduces a modified HS approach combined with an operator of differential evolution - a paradigm of evolutionary computation - to solve optimization problems in reliability engineering. In this context, an example of mixed integer programming in reliability-redundancy design of an over-speed protection system for a gas turbine is evaluated. In this application domain, HS was found to outperform the previously best-known solutions available. ©2009 IEEE.

关键词： Integer programming

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Sample average approximation approach to multi-location transshipment problem with capacitated production

Sample average approximation approach to multi-location tran...

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2009 Winter Simulation Conference, WSC 2009

作者： Özdemir, Deniz Yücesan, Enver Herer, Yale T. Graduate Program in Systems Engineering Universidad Autónoma de Nuevo León San Nicolás de Los Garza N.L. 66450 Mexico Technology and Operations Management Area INSEAD Boulevard de Constance 77305 Fontainebleau Cedex France Faculty of Industrial Engineering and Management Technion Israel Institute of Technology Haifa 32000 Israel

ISBN: (纸本)9781424457700

We consider a supply chain, which consists of N stocking locations and one supplier. The locations may be coordinated through replenishment strategies and lateral transshipments, i.e., transfer of a product among locations at the same echelon level. The supplier has limited production capacity. Therefore, the total amount of product supplied to the N locations is limited in each time period. When total replenishment orders exceed total supply, not all locations will be able to attain their base stock values. Therefore, different allocation rules are considered to specify how the supplier rations its limited capacity among the locations. We team up the modeling flexibility of simulation with sample path optimization to address the multilocation transshipment problem. We solve the sample average approximation problem by random search and by gradient search. With this numerical approach, we can study problems with non-identical costs and correlated demand structures. ©2009 IEEE.

关键词： Location

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A normative self-organizing migrating algorithm for power economic dispatch of thermal generators with valve-point effects and multiple fuels

A normative self-organizing migrating algorithm for power ec...

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IEEE International Conference on systems, Man and Cybernetics

作者： Viviana Cocco Mariani Rodrigo Clemente Thom de Souza Leandro dos Santos Coelho Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paraná Curitiba Parana Brazil Industrial and Systems Engineering PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil

A new class of meta-heuristics called SOMA (Self-Organizing Migrating Algorithm) was proposed in recent literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organizing behavior of groups of individuals in a ¿social environment¿. This paper proposes a modified SOMA approach to solving the economic load dispatch problem of thermal generators with the valve-point effect. To show the performance of the proposed modified SOMA algorithm based on fundamentals of normative knowledge in cultural algorithms, which was applied to test the power economic problem comprised 10 generating units with valve-point effects and multiple fuels for the load demands of 2400 MW. Simulation results show that the classical and modified SOMA algorithms are efficient and have good convergence property when compared with results of other optimization methods reported in the literature.

关键词： Power generation economics Fuel economy Power generation Environmental economics Power system economics industrial economics systems engineering and theory Stochastic processes Evolutionary computation Modeling

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An LMI approach for output feedback Robust Predictive Control using Orthonormal Basis Functions

An LMI approach for output feedback Robust Predictive Contro...

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IEEE Conference on Decision and Control

作者： Humberto X. Araújo Gustavo H. C. Oliveira Department of Electrical Engineering Federal University of Bahia Salvador Bahia Brazil Industrial and Systems Engineering Graduate Program (PPGEPS Pontifícia Universidade Catóica do Paraná Curitiba Parana Brazil

ISBN: (纸本)9781424438716

This paper is focused on the problem of uncertain process control by using RMPC (robust model predictive control). A relevant class of RMPC algorithms is the one characterized by the use of the LMI framework. This field started in the middle of nineties and since then several works applying LMIs in the context of RMPC have been proposed. Most of them assume a polytopic representation of the process uncertainties and require full-state feedback. On the other hand, several works describing the theory and applicability of OBF (orthonormal basis functions) in identification and control fields can be found in the literature. So, the present paper proposes the use of OBF for uncertain process modelling and for RMPC algorithm synthesis. It is shown that, due to the proposed approach, one obtains an output feedback control law, with set-point tracking. This represents an advantage in actual applications. Moreover, well established state feedback RMPC strategies can be reviewed under the OBF modelling perspective. Simulation results illustrate the proposed methodology.

关键词： Output feedback Robust control Predictive control Predictive models Uncertainty State feedback Prediction algorithms Finite impulse response filter Parameter estimation Lyapunov method

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An LMI Approach for Output Feedback Robust Predictive Control using Orthonormal Basis Functions

An LMI Approach for Output Feedback Robust Predictive Contro...

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Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference

作者： Humberto X.Araújo Gustavo H.C.Oliveira Department of Electrical Engineering Federal University of Bahia (UFBA) Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifícia Universidade Católica do Paraná(PUCPR)Rua Imaculada Concei?o

This paper is focused on the problem of uncertain process control by using RMPC（Robust Model Predictive Control）.A relevant class of RMPC algorithms is the one characterized by the use of the LMI *** field started in the middle of nineties and since then several works applying LMIs in the context of RMPC have been *** of them assume a polytopic representation of the process uncertainties and require full-state *** the other hand,several works describing the theory and applicability of OBF（Orthonormal Basis Functions） in identification and control fields can be found in the ***,the present paper proposes the use of OBF for uncertain process modelling and for RMPC algorithm *** is shown that,due to the proposed approach,one obtains an output feedback control law,with set-point *** represents an advantage in actual ***,well established state feedback RMPC strategies can be reviewed under the OBF modelling *** results illustrate the proposed methodology.

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Hardware Architecture for Particle Swarm Optimization Using Floating-Point Arithmetic

Hardware Architecture for Particle Swarm Optimization Using ...

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International Conference on Intelligent systems Design and Applications (ISDA)

作者： Daniel M. Muñoz Arboleda Carlos H. Llanos Leandro dos_S. Coelho Mauricio Ayala-Rincón Department of Mechanical Engineering University of Brasilia Brasília Brazil Industrial and Systems Engineering Graduate Program Pontificial Catholic University of Paraná Curitiba Brazil Departments of Computer Science and Mathematics University of Brasilia Brasília Brazil

High computational cost for solving large engineering optimization problems point out the design of parallel optimization algorithms. Population based optimization algorithms provide parallel capabilities that can be explored by their implementations done directly in hardware. This paper presents a hardware implementation of particle swarm optimization algorithms using an efficient floating-point arithmetic which performs the computations with high precision. All the architectures are parameterizable by bit-width, allowing the designer to choose the suitable format according to the requirements of the optimization problem. Synthesis and simulation results demonstrate that the proposed architecture achieves satisfactory results obtaining a better performance in therms of elapsed time than conventional software implementations.

关键词： Hardware Particle swarm optimization Floating-point arithmetic Computer architecture Design optimization Computational efficiency Design engineering Algorithm design and analysis High performance computing Computational modeling

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Sample average approximation approach to multi-location transshipment problem with capacitated production 09

Sample average approximation approach to multi-location tran...

引用

Simulation Winter Conference

作者： Deniz Özdemir Enver Yücesan Yale T. Herer Graduate Program in Systems Engineering Universidad Autónoma de Nuevo León San Nicolas de los Garza Nuevo Leon Mexico Technology and Operations Management Area INSEAD Fontainebleau France Faculty of Industrial Engineering and Management Technion-Israel Institute of Technology Haifa Israel

ISBN: (纸本)9781424457717

We consider a supply chain, which consists of N stocking locations and one supplier. The locations may be coordinated through replenishment strategies and lateral transshipments, i.e., transfer of a product among locations at the same echelon level. The supplier has limited production capacity. Therefore, the total amount of product supplied to the N locations is limited in each time period. When total replenishment orders exceed total supply, not all locations will be able to attain their base stock values. Therefore, different allocation rules are considered to specify how the supplier rations its limited capacity among the locations. We team up the modeling flexibility of simulation with sample path optimization to address the multi-location transshipment problem. We solve the sample average approximation problem by random search and by gradient search. With this numerical approach, we can study problems with non-identical costs and correlated demand structures.

关键词： Production Costs Optimization methods Modeling Inventory management Technology management engineering management Silver Design optimization Analytical models

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Discrete Differential Evolution with Local Search to Solve the Traveling Salesman Problem: Fundamentals and Case Studies

Discrete Differential Evolution with Local Search to Solve t...

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7th IEEE International Conference on Cybernetic Intelligent systems

作者： Sauer, Joao Guilherme Coelho, Leandro dos Santos Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana (PPGEPS/PUCPR) Curitiba Parana Brazil

ISBN: (纸本)9781424429141

Traveling Salesman Problem (TSP) is one of the most difficult problems in the Combinatorial Optimization area. The goal of TSP is to find one path that can travel between all the nodes (instances) of the graph just once (Hamiltonian tour) in the smallest tour, that is, smallest Euclidian distance. In this context, many other meta-heuristics techniques based on evolutionary algorithms have been propose in literature to solve TSP problems. Differential Evolution (DE) is a relatively new simple evolutionary algorithm, which is an effective adaptive approach to global optimization over continuous search spaces. The design principles of DE are simplicity and efficiency. The most distinct feature of DE is that it mutates vectors by adding weighted. random vector differentials to them. Since its invention. DE has been applied with high success on many numerical optimization problems outperforming other more popular meta-heuristics such as the genetic algorithms. Recently. some researchers extended with success the application of DE to complex combinatorial optimization problems with discrete decision variables such as the traveling salesman problem, the machine layout problem, the now-shop scheduling problem. In this paper, the following discrete DE approaches for the TSP are proposed and evaluated: i) DE approach without local search, ii) DE with local search based on Lin-Kernighan-Heulsgaun (LKH) method, and iii) DE with local search based on Variable Neighborhood Search (VNS) and together with LKH method. Numerical study is carried out using the TSPLIB of test TSP problems. In this context, the computational results are compared with the other results in the recent TSP literature. The obtained results show that LKH method is the best method to reach optimal results for TSPLIB benchmarks, but for largest problems, the ED+VNS improve the quality of obtained results.

关键词： Optimization Traveling salesman problem Evolutionary Algorithm Differential Evolution Variable Neighbor Search Local Search Lin-Kernighan-Heulsgaun

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Quantum Gaussian Particle Swarm Optimization approach for PID controller design in AVR system

Quantum Gaussian Particle Swarm Optimization approach for PI...

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2008 IEEE International Conference on systems, Man and Cybernetics, SMC 2008

作者： Coelho, Leandro Dos Santos Herrera, Bruno Á Vila De Meirelles Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil

During the history of science of computational intelligence, many evolutionary algorithms approaches were proposed having more or less success in solving various optimization problems. In this context, the Particle Swarm Optimization (PSO) is a bio-inspired optimization mechanism based on the metaphor of social behaviour of birds flocking and fish schooling in search for food. Inspired by the classical PSO method and quantum mechanics theories, this work presents a Quantum-behaved PSO (QPSO) approach using Gaussian probability distribution function (G-QPSO). Numerical simulations based on optimized proportional-integral-derivative (PID) control of an automatic regulator voltage system for nominal system parameters and step reference voltage input demonstrate the effectiveness and efficiency of G-QPSO approach. Simulation results of G-QPSO to determine the PID parameters are compared with the classical PSO and QPSO. © 2008 IEEE.

关键词： Quantum theory

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