This paper deals with the problem of the cell size determination in WCDMA-based mobile networks, in multiservice environments. The objective is to obtain the maximum cell size, given a set of services with their corre...
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This paper deals with the problem of the cell size determination in WCDMA-based mobile networks, in multiservice environments. The objective is to obtain the maximum cell size, given a set of services with their corresponding constraints, in terms of quality of service (QoS), binary rate, etc. To achieve this, we have to find the optimal services' load factors which maximizes the cell radius of the system under traffic criteria. We apply an evolutionary programming algorithm to solve the problem, which codifies and evolves the services' load factors. We have compared our approach with an existing algorithm in several multiservice scenarios, improving its solutions in terms of cell size. (c) 2007 Elsevier Ltd. All rights reserved.
JPEG 2000 is an international standard for still image compression, which is based on wavelet transformation and the Daubechies 9/7 filter adopted for lossy compression. Considering that a wavelet filter might be suit...
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JPEG 2000 is an international standard for still image compression, which is based on wavelet transformation and the Daubechies 9/7 filter adopted for lossy compression. Considering that a wavelet filter might be suitable for one image but not for the other in regard to compression quality, in this paper, we propose a novel filter design framework based on the Daubechies 9/7 filter, which employs chaos evolution programming (CEP) to optimize the wavelet filter for both the universal images and each specific image, respectively. The customized filter design is ready to incorporate into the JPEG 2000 compression/decompression since the filter coefficients can be constructed by only one tuning parameter, which can be easily packaged into the modified JPEG 2000 header. Experimental results show that CEP-trained filters achieve higher image quality. (C) 2008 Elsevier B.V. All rights reserved.
Exergoeconomic analysis helps designers to find ways to improve the performance of a system in a cost effective way. Most of the conventional exergoeconomic optimisation methods are iterative in nature and require the...
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Exergoeconomic analysis helps designers to find ways to improve the performance of a system in a cost effective way. Most of the conventional exergoeconomic optimisation methods are iterative in nature and require the interpretation of the designer at each iteration. In this work, a cogeneration system that produces 50 MW of electricity and 15 kg/s of saturated steam at 2.5 bar is optimized using exergoeconomic principles and evolutionary programming. The analysis shows that the product cost, cost of electricity and steam, is 9.9% lower with respect to the base case. This is achieved, however, with 10% increase in capital investment. Moreover, it is important to note that the additional investment can be paid back in 3.23 years. (C) 2007 Elsevier Ltd. All rights reserved.
A novel method, which is called generalized early-time/late-time evolutionary programming (EP)-based CLEAN algorithm, is proposed for simultaneous extraction of the scattering centers and natural resonance frequencies...
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A novel method, which is called generalized early-time/late-time evolutionary programming (EP)-based CLEAN algorithm, is proposed for simultaneous extraction of the scattering centers and natural resonance frequencies of a radar target. This algorithm uses a duality between the temporal late-time response and spectral early-time response. (c) 2007 Wiley Periodicals, Inc.
This paper presents a wire antenna for multi-band WLAN application, designed using the Structure-Based evolutionary programming, and having a very simple geometry. The antenna has been analysed with NEC-2 during the e...
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ISBN:
(纸本)9781467322331
This paper presents a wire antenna for multi-band WLAN application, designed using the Structure-Based evolutionary programming, and having a very simple geometry. The antenna has been analysed with NEC-2 during the evolutionary process, and the outcome of the procedure shows a very good performance, with a -10dB bandwidth that covers the required frequencies for multi-band WLAN applications (2.4/5.2/5.8 GHz) and beyond, and an end-fire gain greater than 11 dB.
The Economic Dispatch problem in a power system is to determine the optimal combination of power outputs for all generating units which will minimize the total fuel cost while satisfying all practical constraints. Now...
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ISBN:
(纸本)9781424424085
The Economic Dispatch problem in a power system is to determine the optimal combination of power outputs for all generating units which will minimize the total fuel cost while satisfying all practical constraints. Now a day with increasing awareness of environmental pollution caused by burning of fossil fuels, emission of pollutants is also a criterion for economic dispatch of the plants. The environmental objective of generation dispatch is to minimize the total environmental cost or the total pollutant emission. Fuzzy logic has been applied in combination with evolutionary programming (EP) to solve various power system problems. For smooth and better convergence in EP the mutation process is improved by fuzzy logic strategy leading to an improved EP technique termed as Fuzzy Mutated evolutionary programming (FMEP). This paper presents an efficient and simple approach for solving the emission constrained economic dispatch problem using FMEP. The convergence and usefulness of the proposed FMEP is demonstrated through its application to a test system. The computational results reveal that the proposed algorithm has excellent convergence characteristics and is superior to the existing methods.
Premature convergence is the fatal shortcoming of traditional evolutionary programming. In this paper, based on the analysis of traditional evolutionary programming premature convergence, an improved multi-subgroup ev...
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ISBN:
(纸本)9780769534947
Premature convergence is the fatal shortcoming of traditional evolutionary programming. In this paper, based on the analysis of traditional evolutionary programming premature convergence, an improved multi-subgroup evolutionary programming(MEP) algorithm Is proposed. In this algorithm, evolution of many subgroups is paralleled performed with different mutation strategy, and then the groups can explore the solution space separately and search the local part detailedly all together. Information Is exchanged when subgroups are reorganized. Simulations based on benchmarks confirm that MEP algorithm is better than classic evolutionary programming algorithm in the aspects of global optimization, convergence speed and the robustness.
The real time communication networks are designed to support multimedia applications requiring quality of services (QoS). The multicasting is needed when number of users want to communicate simultaneously. This paper ...
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ISBN:
(纸本)9781424438051
The real time communication networks are designed to support multimedia applications requiring quality of services (QoS). The multicasting is needed when number of users want to communicate simultaneously. This paper present an approach based on evolutionary programming to solve the QoS constrained multicast routing problem, which is a NP complete problem. The multicast tree is obtained corresponding to optimum (minimum) routing cost subjected to end-to-end delay constraints. The algorithm is tested to obtain optimum multicast trees for different sets of source and destinations on 8-node undirected and 10-node directed networks. The convergence of the proposed algorithm is fast because it relies on mutation and selection and the optimum solution is obtained for both undirected and directed graphs.
This paper describes a new Multi-Objective evolutionary programming (MOEP) method to solve the Combined Economic Emission Dispatch (CEED) and Economic Emission Dispatch (EED) problems. The CEED is a bi-objective optim...
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ISBN:
(纸本)9781424419050
This paper describes a new Multi-Objective evolutionary programming (MOEP) method to solve the Combined Economic Emission Dispatch (CEED) and Economic Emission Dispatch (EED) problems. The CEED is a bi-objective optimization problem that considers two objectives such as fuel cost and NO, emission. It is converted into a single objective optimization problem using weighted sum method. The EED is a three-objective optimization problem that considers the fuel cost, NO, and SO2 emissions as objectives. Non-dominated solution ranking is employed as selection mechanism in the proposed MOEP for the CEED and EED problems. The developed algorithm is tested for a three-unit and a six-unit systems, and six and 30 bus systems. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective problems in a single run.
This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed w...
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ISBN:
(纸本)9781467350723
This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning three PSS-LL parameters, a new Particle Swarm Optimization (PSO) technique called Iteration PSO (IPSO) is proposed. In this method, a new iteration best index is implemented into conventional PSO in order to enhance the quality of the solution. Based on eigenvalues and damping ratio results, it is confirmed that the proposed technique is more efficient than conventional PSO in improving the angle stability of the system. Comparison between IPSO, PSO and evolutionary programming (EP) optimization techniques showed that the proposed computation approach give better solution and faster computation time.
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