Optimal reconfiguration of Radial Distribution System (RDS) is done under the umbrella of Supervisory Control and Data Acquisition (SCADA) systems to achieve the best voltage profile and minimal kW losses amongst seve...
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Optimal reconfiguration of Radial Distribution System (RDS) is done under the umbrella of Supervisory Control and Data Acquisition (SCADA) systems to achieve the best voltage profile and minimal kW losses amongst several objectives. This problem requires the determination of the best combination of feeders from each loop in the RDS to be switched out such that the resulting RDS gives the optimal performance in the chosen circumstance. The problem has a discontinuous solution space and certain problem variables assume discrete values of zero or one. This paper proposes a method that uses fuzzy adaptation of evolutionary programming (FEP) as a solution technique. FEP technique has been chosen as it is particularly suited while solving optimization problems with discontinuous solution space and when the global optimum is desired. Fuzzy adaptation of EP is necessitated while considering optimization of multiple objectives. The proposed method is tested on established RDS and results are presented. (C) 2003 Elsevier Ltd. All rights reserved.
This letter introduces a new multiuser detection scheme which uses evolutionary programming (EP) to detect the user bits based on the maximum-likelihood decision rule. The major advantage of the proposed detector is t...
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This letter introduces a new multiuser detection scheme which uses evolutionary programming (EP) to detect the user bits based on the maximum-likelihood decision rule. The major advantage of the proposed detector is that it has a lower computational complexity compared to other popular evolutionary-algorithm-based detectors. The simulation results show that the EP has always converged to the optimum solution with a small number of generations. The simulated average computational time performance demonstrates that this approach achieves practical ML performance with polynomial complexity in the number of users.
Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuelcost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem...
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Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuelcost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. This biobjective CEED problem is converted into a single objective function using a price penalty factor approach. A novel modified price penalty factor is proposed to solve the CEED problem. In this paper, evolutionary computation (EC) methods such as genetic algorithm (GA), micro GA, (NIGA), and evolutionary programming (EP) are applied to obtain ELD solutions for three-, six-, and 13-unit systems. Investigations showed that EP? was better arnong EC methods in solving the ELD problem. EP-based CEED. problem has been tested on IEEE 14-, 30-, and 118-bus systems with and without line flow constraints. A nonlinear scaling factor is also included in EP algorithm to improve the convergence performance for the 13 units and IEEE test systems. The solutions obtained are quite encouraging and useful in the economic emission environment.
The maintenance scheduling problem has several uncertainties associated with it. This paper presents a fuzzy model for the integrated generation and transmission maintenance scheduling problem (MS) that accounts for s...
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The maintenance scheduling problem has several uncertainties associated with it. This paper presents a fuzzy model for the integrated generation and transmission maintenance scheduling problem (MS) that accounts for such uncertainties, and introduces a solution technique to solve for the optimal schedule. This technique is based on-evolutionary programming (EP) to find a near-optimal solution and the Hill-Climbing (HCT) method to maintain feasibility during the solution process. It also uses a, fuzzy comparison technique developed by the authors to compare individuals. The proposed technique generates fuzzy ranges for the maintenance and production costs that reflect the problem uncertainties. The paper includes test results on the IEEE 118-bus system with 33 generating units and 179 transmission lines. Results are encouraging and indicate the viability of the proposed technique.
In this paper a novel method for selecting optimal branch conductor of radial distribution feeders based on evolutionary programming (EP) has been presented. The aim of optimal conductor size selection is to select a ...
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ISBN:
(纸本)0780381629
In this paper a novel method for selecting optimal branch conductor of radial distribution feeders based on evolutionary programming (EP) has been presented. The aim of optimal conductor size selection is to select a feeder so as to minimize an objective function, which is sum of capital investment and capitalized energy loss costs. Optimal conductor type is determined for each feeder by using EP. Voltage constraints and maximum current carrying capacity of the conductors are also incorporated in the algorithm. One example is presented to demonstrate the effectiveness of the proposed method in the draft paper.
In this paper, a robust optimization algorithm based on combined evolutionary programming (EP)/Cluster analysis is presented.. In order to alleviate the problem of premature convergence when the objective function is ...
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ISBN:
(纸本)0780377818
In this paper, a robust optimization algorithm based on combined evolutionary programming (EP)/Cluster analysis is presented.. In order to alleviate the problem of premature convergence when the objective function is highly multimodal, an efficient algorithm is developed that combines the conventional EP with clustering method. In this approach, the cluster analysis provides an accurate estimate on the size and location of clusters of subpopulations, which are formed during the optimization process. This information is then used to put pressure on the members of each individual cluster for sharing the fitness value, similar to the approach used in the well-known niching technique. The developed algorithm has been successfully applied to many mathematical test problems as well as several RF/microwave engineering problems. The results for a multimodal function optimizations and an example on the synthesis of a microwave multiple-coupled resonator for wireless application using optimization approach are presented.
Fuzzy logic controllers have been proven to be an effective means of solving real world control issues. One of the difficulties in the construction of fuzzy controllers is the design of the rule base under which they ...
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ISBN:
(纸本)0780379187
Fuzzy logic controllers have been proven to be an effective means of solving real world control issues. One of the difficulties in the construction of fuzzy controllers is the design of the rule base under which they operate. This paper investigates the application of evolutionary programming as an iterative learning process for the fuzzy rule base. This approach is applied to the problem of an elevator control system. The system is optimized for efficiency and smoothness by encouraging higher velocities with minimal changes in acceleration, and by discouraging violations of the design parameters for the system. The performance of the evolved system compares favorably to that of fuzzy controllers designed using traditional methods.
In this paper, we exploit the capability of evolutionary programming for construction and training neural networks, independent of the applied models of the neurons. The main application of this algorithm is training ...
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ISBN:
(纸本)0780377818
In this paper, we exploit the capability of evolutionary programming for construction and training neural networks, independent of the applied models of the neurons. The main application of this algorithm is training neural networks with elaborated models for neurons. For instance when because of implementation limitations a deviation from ideal models is mandatory, this algorithm can be used to take these deviations into account during the training process. The functionality of the proposed algorithm is demonstrated by training a neural controller with non-conventional neurons.
This paper presents the application of evolutionary programming to combined environmental/economic dispatch. The economic and emission objectives are combined linearly to form a single bi-criterion objective. The impl...
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This paper presents the application of evolutionary programming to combined environmental/economic dispatch. The economic and emission objectives are combined linearly to form a single bi-criterion objective. The implementation of evolutionary programming (EP) approach is demonstrated by an example. Its results are compared with fuzzy logic controlled genetic algorithms. The test results prove that EP method is one of the most effective methods available for solving bi-objective optimisation problems.
A evolutionary programming is proposed in this paper to automatically design neural networks (NNs) ensembles. Based on negative correlation learning, different individual NNs in the ensemble can learn to subdivide the...
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ISBN:
(纸本)0780378652
A evolutionary programming is proposed in this paper to automatically design neural networks (NNs) ensembles. Based on negative correlation learning, different individual NNs in the ensemble can learn to subdivide the task and thereby solve it more efficiently and elegantly. At the same time, different individual NNs are always to rind the best collaboration connection during the evolutionary process. In addition, the architecture of each NN in the ensemble and the size of the ensemble need not to be predefined. The simulation results show that the proposed method in this paper is valid.
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