In this paper, the social behaviors of fish swarm were classified in four ways: foraging behavior, stray behavior, reproductive behavior, and escaping behavior. Inspired by this, a novel artificial fish swarm algorith...
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In this paper, the social behaviors of fish swarm were classified in four ways: foraging behavior, stray behavior, reproductive behavior, and escaping behavior. Inspired by this, a novel artificial fish swarm algorithm (NAFSA) was proposed, which integrated the merits of the self-adaptation strategy, mutation strategy and hybrid strategy into the social behaviors of fish swarm. In the case of mutation strategy, the cloud theory was introduced into the escaping behavior, and the basic cloud generator was used as the mutation operator because of the properties of randomness and stable tendency of a normal cloud model. For the hybrid strategy, the selection, crossover and mutation operator in evolutionary algorithm were applied to define the reproductive ability of an artificial fish. Furthermore, the parameters of Step and Visual were developed in forms of hyperbolic tangent function to adjust the optimize performance dynamically during iterations process. Finally, ten standard test functions are used as the benchmark to validate the effectiveness of the NAFSA. Experimental results confirmed the superiority of NAFSA in terms of both solution quality and convergence speed.
Design for assembly (DFA) has proved its success in manufacturing to face the market challenge. But the assembly process parameters were rarely concerned in the design for assembly. Aimed at this problem, an algorithm...
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ISBN:
(纸本)9780878494705
Design for assembly (DFA) has proved its success in manufacturing to face the market challenge. But the assembly process parameters were rarely concerned in the design for assembly. Aimed at this problem, an algorithm for design for automated assembly of circular parts was proposed. This algorithm can help designer to select the optimal process parameters, such as dimension tolerance of mating parts, location precision of assembly device and so on, subject to budgetary constraints. Finally a case is employed to explain the optimal course.
Artificial neural network has been widely used at present to solve many engineering problems. However, simple neural network model is hard to get the desired result. This paper proposes one combined model of AHP (Anal...
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Artificial neural network has been widely used at present to solve many engineering problems. However, simple neural network model is hard to get the desired result. This paper proposes one combined model of AHP (Analytic Hierarchy Process) and BPNN (Back Propagation Neuron Network) based on data mining. This model can improve the rate of convergence and the reliability of results. The validity of this method has been demonstrated with data from an existing oilfield in north-west China for predicting the rate of penetration (ROP). Furthermore, the model can be used in post-well analysis to identify areas where potential drilling performance was not achieved, and help in identifying improvements for future projects.
Hybrid optimization and antioptimization of the buckling load of composite cylindrical shells is conducted. The methodology, which has been developed in previous works, is applied to a set of cylindrical composite she...
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Hybrid optimization and antioptimization of the buckling load of composite cylindrical shells is conducted. The methodology, which has been developed in previous works, is applied to a set of cylindrical composite shells, tested at German Aerospace Center. Furthermore, the existing approach is enhanced to fit within the design-optimization scheme. The shells possess traditional imperfections in the form of Fourier series coefficients of their initial imperfection profile. Additionally, two nontraditional imperfections are included in the analysis. The available experimental data is enclosed by either 11-dimensional hyperrectangle or hyperellipsoid. The minimum buckling load of the ensemble of such shells is determined by the antioptimization procedure. Then, this minimum load is maximized by varying the laminate angle. It is shown that the proposed method is a viable and relatively simple alternative to probabilistic approaches and successfully supplements them. It is shown that the proposed method is a successful supplement to probabilistic methods and the deterministic single-buckle approach, because it is deterministic in nature and thus could appeal to engineers and investigators alike, and it takes into account the actual scatter of input data.
The bottleneck assignment (BA) and the generalized assignment (GA) problems and their exact solutions are explored in this paper. Firstly, a determinant elimination (DE) method is proposed based on the discussion of t...
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ISBN:
(纸本)9783037855454
The bottleneck assignment (BA) and the generalized assignment (GA) problems and their exact solutions are explored in this paper. Firstly, a determinant elimination (DE) method is proposed based on the discussion of the time and space complexity of the enumeration method for both BA and GA problems. The optimization algorithm to the pre-assignment problem is then discussed and the adjusting and transformation to the cost matrix is adopted to reduce the computational complexity of the DE method. Finally, a synthesis method for both BA and GA problems is presented. The numerical experiments are carried out and the results indicate that the proposed method is feasible and of high efficiency.
Computational fluid dynamics has been coupled with an optimization algorithm to design a crucial component in a high-voltage circuit breaker (CB). The multiobjective optimization has been used to search for an optimum...
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Computational fluid dynamics has been coupled with an optimization algorithm to design a crucial component in a high-voltage circuit breaker (CB). The multiobjective optimization has been used to search for an optimum design for two switching cases simultaneously, revealing potential tradeoffs or conflicts. The use and applicability of response surface methodology (RSM) is presented.
This paper deals with the development of feed back controller design for a voltage controlled induction motor drive employing an enhanced optimization algorithm derived from the principles of foraging of natural ants....
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This paper deals with the development of feed back controller design for a voltage controlled induction motor drive employing an enhanced optimization algorithm derived from the principles of foraging of natural ants. A linearized incremental model of a voltage controlled induction motor drive is shown to exhibit parameter variation at different operating points of the drive system. A PI-controller derived at a typical operating point using traditional methods does not give satisfactory performance for a wide bandwidth of load and reference speed changes. The newly developed Ant Colony optimization technique enforces continuous exploration of the solution space and identifies optimal controller structure. The development of optimization algorithm and its application to feed back controller design for a variable voltage induction motor drive is well documented in this paper. Experimental and simulation results are presented to validate the efficacy of the optimized controller. (C) 2012 Elsevier B.V. All rights reserved.
In order to optimize the knapsack problem further, this paper proposes an innovative model based on dynamic expectation efficiency, and establishes a new optimization algorithm of 0-1 knapsack problem after analysis a...
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In order to optimize the knapsack problem further, this paper proposes an innovative model based on dynamic expectation efficiency, and establishes a new optimization algorithm of 0-1 knapsack problem after analysis and research. Through analyzing the study of 30 groups of 0-1 knapsack problem from discrete coefficient of the data, we can find that dynamic expectation model can solve the following two types of knapsack problem. Compared to artificial glowworm swam algorithm, the convergence speed of this algorithm is ten times as fast as that of artificial glowworm swam algorithm, and the storage space of this algorithm is one quarter that of artificial glowworm swam algorithm. To sum up, it can be widely used in practical problems.
A new version of progressive resolution optimizer (PRO) with an option of air cavity correction has been implemented for RapidArc volumetric-modulated arc therapy (RA). The purpose of this study was to compare the per...
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A new version of progressive resolution optimizer (PRO) with an option of air cavity correction has been implemented for RapidArc volumetric-modulated arc therapy (RA). The purpose of this study was to compare the performance of this new PRO with the use of air cavity correction option (PRO10_air) against the one without the use of the air cavity correction option (PRO10_no-air) for RapidArc planning in targets with low-density media of different sizes and complexities. The performance of PRO10_no-air and PRO10_air was initially compared using single-arc plans created for four different simple heterogeneous phantoms with virtual targets and organs at risk. Multiple-arc planning of 12 real patients having nasopharyngeal carcinomas (NPC) and ten patients having non-small cell lung cancer (NSCLC) were then performed using the above two options for further comparison. Dose calculations were performed using both the Acuros XB (AXB) algorithm with the dose to medium option and the analytical anisotropic algorithm (AAA). The effect of using intermediate dose option after the first optimization cycle in PRO10_air and PRO10_no-air was also investigated and compared. Plans were evaluated and compared using target dose coverage, critical organ sparing, conformity index, and dose homogeneity index. For NSCLC cases or cases for which large volumes of low-density media were present in or adjacent to the target volume, the use of the air cavity correction option in PRO10 was shown to be beneficial. For NPC cases or cases for which small volumes of both low-and high-density media existed in the target volume, the use of air cavity correction in PRO10 did not improve the plan quality. Based on the AXB dose calculation results, the use of PRO10_air could produce up to 18% less coverage to the bony structures of the planning target volumes for NPC cases. When the intermediate dose option in PRO10 was used, there was negligible difference observed in plan quality between optimizations
This paper presents an algorithm for optimal placement and size of the Distributed energy resources (DERs) considering system loss minimization and voltage profile improvement as objective functions. DERs- are the ene...
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ISBN:
(纸本)9781467349215
This paper presents an algorithm for optimal placement and size of the Distributed energy resources (DERs) considering system loss minimization and voltage profile improvement as objective functions. DERs- are the energy resources which contain renewable energy resources such as wind, solar and fuel cell and some artificial models like micro turbines, gas turbines, diesel engines, sterling engines, and internal combustion reciprocating engines. Combinations of DER studies and for every combination, indices, active and reactive losses and voltage profiles are studied. To optimize the objective function, new optimization technique called Bat algorithm(BA) is proposed. The Bat algorithm is tested on 37-bus distribution system with different load models like residential, Industrial, Commercial and Mixed loads. For all cases current injection based distribution load flow method is used.
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