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Itinerary determination of imprecise mobile agents with firm deadline

Web Intelligence and Agent systems 2008年第4期6卷 421-439页

作者： Rech, Luciana Montez, Carlos De Oliveira, Rômulo Silva Department of Automation and Systems Engineering Graduate Program in Electrical Engineering Federal University of Santa Catarina P.O. Box 47 CEP 88040-900 Florianópolis SC Brazil

In some applications, as part of a mobile agent mission, there may be the necessity of meeting a firm end-to-end deadline, although with some itinerary flexibility due to optional resources. This paper proposes an execution model based on the concept of imprecise mobile agents with timing constraints. In this paper it is considered an execution model where agents do not previously know their itineraries. The imprecise mobile agent may choose among alternative and/or optional resources. The objective is to propose and to evaluate heuristics to be used individually or in pairs by imprecise mobile agents that must accomplish a mission within a firm deadline. © 2008 - IOS Press and the authors. All rights reserved.

关键词： Mobile agents

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Economic dispatch optimization using hybrid chaotic particle swarm optimizer

Economic dispatch optimization using hybrid chaotic particle...

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2007 IEEE International Conference on systems, Man, and Cybernetics, SMC 2007

作者： Dos Santos Coelho, Leandro Mariani, Viviana Coceo Industrial and Systems Engineering Graduate Program - PPGEPS Automation and Systems Laboratory Pontifical Catholic University of Paraná Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program PUCPR/PPGEM Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)1424409918

Particle swarm optimization (PSO) is a population-based stochastic optimization technique, originally developed by Eberhart and Kennedy, inspired by simulation of a social psychological metaphor instead of the survival of the fittest individual. In PSO, the system (swarm) is initialized with a population of random solutions (particles) and searches for optima using cognitive and social factors by updating generations. PSO has been successfully applied to a wide range of applications, mainly in solving continuous nonlinear optimization problems. Based on the PSO and chaos theories, this paper discusses the use of a chaotic PSO approach hybridized with an Implicit Filtering (IF) technique to optimize performance of economic dispatch problems. The chaotic PSO with chaos sequences is the global optimizer and the IF is used to fine-tune the chaotic PSO run in sequential manner. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. © 2007 IEEE.

关键词： Particle swarm optimization (PSO)

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Economic dispatch optimization using hybrid chaotic particle swarm optimizer

Economic dispatch optimization using hybrid chaotic particle...

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IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Viviana Cocco Mariani Industrial and Systems Engineering Graduate Program-PPGEPS Automation and Systems Laboratory PUCPR/PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil Mechanical Engineering Graduate Program PUCPR/PPGEM Pontifical Catholic University of Paraná Curitiba Parana Brazil

Particle swarm optimization (PSO) is a population-based stochastic optimization technique, originally developed by Eberhart and Kennedy, inspired by simulation of a social psychological metaphor instead of the survival of the fittest individual. In PSO, the system (swarm) is initialized with a population of random solutions (particles) and searches for optima using cognitive and social factors by updating generations. PSO has been successfully applied to a wide range of applications, mainly in solving continuous nonlinear optimization problems. Based on the PSO and chaos theories, this paper discusses the use of a chaotic PSO approach hybridized with an implicit filtering (IF) technique to optimize performance of economic dispatch problems. The chaotic PSO with chaos sequences is the global optimizer and the IF is used to fine-tune the chaotic PSO run in sequential manner. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects.

关键词： Chaos Particle swarm optimization Fuel economy Stochastic processes Psychology Social factors Filtering theory System testing Thermal loading Cost function

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Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect (vol 21, pg 989, 2006)

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IEEE TRANSACTIONS ON POWER systems 2006年第3期21卷 1465-1465页

作者： dos Santos Coelho, Leandro Cocco Mariani, Viviana Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPRJCCET/PPGEPSILAS Pontifical Catholic University of Paraná 802 15-901 Curitiba Paraná Brazil Mechanical Engineering Graduate Program PUCPRJCCETIPPGEM Pontifical Catholic University of Paraná 802 15-901 Curitiba Paraná Brazil

Evolutionary algorithms are heuristic methods that have yielded promising results for solving nonlinear, nondifferentiable, and multi-modal optimization problems in the power systems area. The differential evolution (DE) algorithm is an evolutionary algorithm that uses a rather greedy and less stochastic approach to problem solving than do classical evolutionary algorithms, such as genetic algorithms, evolutionary programming, and evolution strategies. DE also incorporates an efficient way of self-adapting mutation using small populations. The potentialities of DE are its simple structure, easy use, convergence property, quality of solution, and robustness. This paper proposes a new approach for solving economic load dispatch problems with valve-point effect. The proposed method combines the DE algorithm with the generator of chaos sequences and sequential quadratic programming (SQP) technique to optimize the performance of economic dispatch problems. The DE with chaos sequences is the global optimizer, and the SQP is used to fine-tune the DE run in a sequential manner. The combined methodology and its variants are validated for two test systems consisting of 13 and 40 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other state-of-the-art algorithms in solving load dispatch problems with the valve-point effect. [ABSTRACT FROM AUTHOR]

关键词： Chaotic sequences differential evolution (DE) economic dispatch evolutionary algorithms optimization power generation valve-point effect

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Chaotic differential evolution applied to electromagnetics optimization

Chaotic differential evolution applied to electromagnetics o...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Dos Santos Coelho, Leandro Mariani, Viviana Cocco Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Imaculada Conceicao 1155 80215-901 Curitiba Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program PUCPR/PPGEM Imaculada Conceicao 1155 80215-901 Curitiba Brazil

ISBN: (纸本)1424403200

This work presents a new global optimization algorithm based on differential evolution (DE) method and DE combined with chaotic sequences (DEC) given by logistic map. In this paper, the optimal shape design of Loney's solenoids benchmark problem is carried out by DE and DEC algorithms. The results of DE and DEC approaches are also investigated and their performance compared with those reported in the literature. © 2006 IEEE.

关键词： Chaos theory

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Use of cultural particle swarm optimization for Loney's Solenoids design

Use of cultural particle swarm optimization for Loney's Sole...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Coelho, Leandro Dos Santos Mariani, Viviana Cocco Pontifical Catholic University of Paraná Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/PPGEPS/LAS Imaculada Conceicao 1155 80215-901 Curitiba Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program PUCPR/PPGEM Imaculada Conceiçao 1155 80215-901 Curitiba Brazil

ISBN: (纸本)1424403200

This work presents the use of particle swarm optimization (PSO) techniques with the particles' population space based on normative knowledge of cultural algorithms (CA). In this work, the optimal shape design of Loney's solenoids benchmark problem is carried out by PSO, PSO-CA, Gaussian PSO and Gaussian PSO-CA approaches. ©2006 IEEE.

关键词： Solenoids

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An efficient particle swarm optimization approach based on cultural algorithm applied to mechanical design

An efficient particle swarm optimization approach based on c...

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2006 IEEE Congress on Evolutionary Computation, CEC 2006

作者： Dos Coelho, Leandro Santos Mariani, Viviana Coceo Pontifical Catholic University of Paraná Production and Systems Eng. Graduate Program Automation and Systems Laboratory Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil

ISBN: (纸本)0780394879

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the swarm intelligence theory, this paper discusses the use of PSO approaches using an operator and based on the Gaussian probability distribution function as a population space of a cultural algorithm, called cultural Gaussian PSO (GPSO-CA). Cultural algorithms are mechanisms that incorporate domain knowledge obtained during the evolutionary process, which increase the efficiency of the search process. These approaches are employed in a well-studied continuous optimization problem of mechanical engineering design. © 2006 IEEE.

关键词： Global optimization

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Electromagnetic device optimization using improved differential evolution methods

Electromagnetic device optimization using improved different...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Coelho, Leandro Dos Santos Alotto, Piergiorgio Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Imaculada Conccicao 1155 80215-901 Curitiba Paraná Brazil Dip. Ingegneria Eleurica University di Padova Italy

ISBN: (纸本)1424403200

Recently, evolutionary algorithms (e.g. genetic algorithms, evolutionary programming, and evolution strategies) have proven to be useful tools for the optimization of difficult problems in electromagnetics. Differential evolution (DE) is one comparatively simple variant of an evolutionary algorithm using floating-point encoding and few control parameters. This work presents improved DE algorithms based on linearly time varying control parameters, sinusoidal functions, and diversity analysis of population. © 2006 IEEE.

关键词： Electromagnets

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Particle Swarm Optimization with Quasi-Newton Local Search for Solving Economic Dispatch Problem

Particle Swarm Optimization with Quasi-Newton Local Search f...

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IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Viviana Cocco Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Curitiba Brazil

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the swarm intelligence theory, this paper discusses the use of PSO with a Quasi-Newton (QN) local search method. The PSO is used to produce good potential solutions, and the QN is used to fine-tune of final solution of PSO. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects.

关键词： Particle swarm optimization Power generation Power generation economics Fuel economy Cost function Equations Power system economics System testing Character generation Constraint optimization

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Use of Cultural Particle Swarm Optimization for Loney's Solenoids Design

Use of Cultural Particle Swarm Optimization for Loney's Sole...

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IEEE Conference on Electromagnetic Field Computation

作者： L. dos Santos Coelho V. Cocco Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Brazil Mechanical Engineering Graduate Program PUCPR/PPGEM Pontifical Catholic University of Paraná Curitiba Brazil

关键词： Cultural differences Particle swarm optimization Solenoids Optimization methods Design optimization Algorithm design and analysis Gaussian distribution Probability distribution Random number generation Equations

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