In this letter, a new optimization algorithm, the Modified compact Genetic algorithm (M-cGA) is introduced and applied to the synthesis of thinned arrays. The M-cGA has been derived from the compact Genetic algorithm ...
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In this letter, a new optimization algorithm, the Modified compact Genetic algorithm (M-cGA) is introduced and applied to the synthesis of thinned arrays. The M-cGA has been derived from the compact Genetic algorithm (cGA), properly modified and improved by implementing more than one probability vector (PV) and adding suitable learning scheme between these PVs. The so-obtained algorithm has been applied to the optimized synthesis of different-size linear and planar thinned arrays: In all the considered cases, it outperforms not only the cGA, but also the other optimization schemes previously applied to this kind of problem, both in terms of goodness of the solution (minimization of the peak sidelobe level) and of computational cost.
Space debris constitutes a major and growing threat to space missions. To assess the probability of collision, the time of closest approach between the spacecraft and the debris must first be calculated. This paper pr...
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Space debris constitutes a major and growing threat to space missions. To assess the probability of collision, the time of closest approach between the spacecraft and the debris must first be calculated. This paper presents three new methods for the calculation of the time of closest approach. The first is a surrogate-based optimization algorithm, using the Alfano-Negron Close Approach Software as the model, allowing a compromise between calculation speed and accuracy. The second is a generalization of this software, treating a cloud of debris as a continuous object and searching for the time of closest approach over initial conditions as well as time. The third uses Alfano-Negron Close Approach Software generalization as a model for surrogate-based optimization. Using the third method, a strategy for safe operation of a spacecraft cluster in a debris-rich environment is proposed. All methods are demonstrated and compared. It is shown that Alfano-Negron Close Approach Software and the generalization thereof are very fast in estimating the time of closest approach, and that the surrogate-based optimization algorithms are somewhat slower, but are highly accurate.
Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the 2.0-cm ...
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Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the 2.0-cm rule from a new point of view. Here, we try to find the optimal threshold based on the differences between the gene expression profiles of the T1 and T2 groups (as defined by the threshold). We developed a numerical algorithm to measure the overall differential gene expression between patients with smaller tumors and those with larger tumors among multiple expression datasets from different studies. We confirmed the performance of the proposed algorithm by a simulation study and then applied it to three different studies conducted at two Norwegian hospitals. We found that the maximum difference in gene expression is obtained at a threshold of 2.2-2.4 cm, and we confirmed that the optimum threshold was over 2.0 cm, as indicated by a validation study using five publicly available expression datasets. Furthermore, we observed a significant differentiation between the two threshold groups in terms of time to local recurrence for the Norwegian datasets. In addition, we performed an associated network and canonical pathway analyses for the genes differentially expressed between tumors below and above the given thresholds, 2.0 and 2.4 cm, using the Norwegian datasets. The associated network function illustrated a cellular assembly of the genes for the 2.0-cm threshold: an energy production for the 2.4-cm threshold and an enrichment in lipid metabolism based on the genes in the intersection for the 2.0- and 2.4-cm thresholds.
Node attributes play an important role in shaping network structures, but are generally ignored in transformations of structural balance. A fully signed network consisting of signs of edges and nodes expresses both pr...
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Node attributes play an important role in shaping network structures, but are generally ignored in transformations of structural balance. A fully signed network consisting of signs of edges and nodes expresses both properties of relationship and node attributes. In this article, we generalize the definition of structural balance in fully signed networks. We transform the unbalanced fully signed network by not only changing signs of edges but also changing the signs of nodes. We propose a memetic algorithm to transform unbalanced networks at the lowest cost. Experiments show that our algorithm can solve this problem efficiently, and different node attribute assignments may lead to different optimized structures. (C) 2016 Wiley Periodicals, Inc.
Structural optimization of quaternary Ag-Au-Pd-Pt clusters up to 38 atoms is performed using adaptive immune optimization algorithm, and the Gupta many-body potential is adopted to model interatomic interaction. By fi...
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Structural optimization of quaternary Ag-Au-Pd-Pt clusters up to 38 atoms is performed using adaptive immune optimization algorithm, and the Gupta many-body potential is adopted to model interatomic interaction. By fixing the atomic number of three types and varying the number of one type in quaternary clusters, geometrical effects by different types of noble metals are investigated. Results show that most configurations present the growth pattern based on the 19-atom double icosahedra, however, the structural transition model induced by increasing the number of the fourth noble atom is found to be different. Furthermore, the order parameter indicates that in quaternary clusters Ag and Au atoms mainly occupy the surface sites, Pd atoms tend to be in the middle shell, and the inner shell is located by Pt atoms. The study of the number of bonds indicates that Ag and Au atoms prefer scattering and forming a circle on the surface, respectively. (C) 2016 Elsevier B.V. All rights reserved.
Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human...
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Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human experts. A modified genetic-algorithm-based approach is proposed in this paper to solve this problem. The simplified layout space is first divided into three- dimensional （3D） grids to build its mathematical model. Branch pipes in layout space are regarded as a combination of several two-point pipes, and the pipe route between two connection points is generated using an improved maze algorithm. The coding of branch pipes is then defined, and the genetic operators are devised, especially the complete crossover strategy that greatly accelerates the convergence speed. Finally, simulation tests demonstrate the performance of proposed method.
Cost optimization is one of the key elements of the EU regulatory framework concerning the energy performance of buildings. From this economic point of view, the optimum occurs when the global cost over the lifecycle ...
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Cost optimization is one of the key elements of the EU regulatory framework concerning the energy performance of buildings. From this economic point of view, the optimum occurs when the global cost over the lifecycle of a building is minimized, and the cost-optimal energy performance level is that related to the minimum global cost. To determine this cost-optimal level by evaluating a great number of design alternatives, it is necessary to exploit automated optimization search procedures. The work presented here concerns the application of cost optimal methodology, as defined by European regulation, to a low-consumption single-family house in France. The calculation is performed through an iterative input-output process in a computing environment that combines TRNSYS (R), transient system simulation tool, with GenOpt (R), generic optimization program. The methodology that was adopted allowed around ten thousand building configurations to be simulated in a reasonable computational time. The paper focuses on how the energy system affects the technical and economic optimal design solutions of the building in two different French climate conditions. (C) 2016 Elsevier B.V. All rights reserved.
A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of u...
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A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory. (C) 2016 Elsevier Ltd. All rights reserved.
In the analysis of structural reliability, often a sequence of design points associated with a set of thresholds are sought in order to determine the tail distribution of a response quantity. In this paper, after a br...
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In the analysis of structural reliability, often a sequence of design points associated with a set of thresholds are sought in order to determine the tail distribution of a response quantity. In this paper, after a brief review of methods for determining the design point, an inverse reliability method named the lambda-method is introduced for efficiently determining the sequence of design points. The lambda-method uses Broyden's "good" method to solve a set of nonlinear simultaneous equations to,find the design points for the values of an implicitly defined threshold that is associated with parameter lambda. In a special parameter setting, the lambda parameter equals the reliability index, thus allowing convenient implementation of the method. Three numerical examples illustrate the accuracy and efficiency of the proposed method. (C) 2015 Elsevier Ltd. All rights reserved.
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