A new constraint handling method for wind farm layout optimization with lands owned by different owners

For wind farm optimizations with lands belonging to different owners, the traditional penalty method is highly dependent on the type of wind farm land division. The application of the traditional method can be cumbersome if the divisions are complex. To overcome this disadvantage, a new method is proposed in this paper for the first time. Unlike the penalty method which requires the addition of penalizing term when evaluating the fitness function, it is achieved through repairing the infeasible solutions before fitness evaluation. To assess the effectiveness of the proposed method on the optimization of wind farm, the optimizing results of different methods are compared for three different types of wind farm division. Different wind scenarios are also incorporated during optimization which includes (i) constant wind speed and wind direction; (ii) various wind speed and wind direction, and; (iii) the more realisticWeibull distribution. Results show that the performance of the new method varies for different land plots in the tested cases. Nevertheless, it is found that optimum or at least close to optimum results can be obtained with sequential land plot study using the new method for all cases. It is concluded that satisfactory results can be achieved using the proposed method. In addition, it has the advantage of flexibility in managing the wind farm design, which not only frees users to define the penalty parameter but without limitations on the wind farm division.

Structural optimization approach for specially shaped composite tank in spacecrafts

This study proposes an optimized approach of designing in which a model specially shaped composite tank for spacecrafts is built by applying finite element analysis. The composite layers are preliminarily designed by combining quasi-network design method with numerical simulation, which determines the ratio between the angle and the thickness of layers as the initial value of the optimized design. By adopting an adaptive simulated annealing algorithm, the angles and the numbers of layers at each angle are optimized to minimize the weight of structure. Based on this, the stacking sequence of composite layers is formulated according to the number of layers in the optimized structure by applying the enumeration method and combining the general design parameters. Numerical simulation is finally adopted to calculate the buckling limit of tanks in different designing methods. This study takes a composite tank with a cone-shaped cylinder body as example, in which ellipsoid head section and outer wall plate are selected as the object to validate this method. The result shows that the quasi-network design method can improve the design quality of composite material layer in tanks with complex preliminarily loading conditions. The adaptive simulated annealing algorithm can reduce the initial design weight by 30%, which effectively probes the global optimal solution and optimizes the weight of structure. It can be therefore proved that, this optimization method is capable of designing and optimizing specially shaped composite tanks with complex loading conditions.

A survey: Particle Swarm Optimization based algorithms to solve premature convergence problem

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

A robust optimization approach for index tracking problem

Index tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this paper, quadratic as well as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input data using a tractable robust framework that controls the level of conservatism while maintaining linearity. The linearity of the proposed robust optimization models allows a simple implementation of an ordinary optimization software package to find the optimal robust solution. The proposed model of this paper employs Morgan Stanley Capital International Index as the target index and the results are reported for six national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of the proposed models is evaluated using several financial criteria e.g. information ratio, market ratio, Sharpe ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of tracking error while raising values of portfolio performance measures.

Balancing exploration and exploitation in particle swarm optimization on search tasking

In this study we present a combinatorial optimization method based on particle swarm optimization and local search algorithm on the multi-robot search system. Under this method, in order to create a balance between exploration and exploitation and guarantee the global convergence, at each iteration step if the distance between target and the robot become less than specific measure then a local search algorithm is performed. The local search encourages the particle to explore the local region beyond to reach the target in lesser search time. Experimental results obtained in a simulated environment show that biological and sociological inspiration could be useful to meet the challenges of robotic applications that can be described as optimization problems.

Numerical optimization of soft-mold aided co-curing process of advanced grid-stiffened composite structures

The co-curing process for advanced grid-stiffened (AGS) composite structure is a promising manufacturing process, which could reduce the manufacturing cost, augment the advantages and improve the performance of AGS composite structure. An improved method named soft-mold aided co-curing process which replaces the expansion molds by a whole rubber mold is adopted in this paper. This co-curing process is capable to co-cure a typical AGS composite structure with the manufacturer’s recommended cure cycle (MRCC). Numerical models are developed to evaluate the variation of temperature and the degree of cure in AGS composite structure during the soft-mold aided co-curing process. The simulation results were validated by experimental results obtained from embedded temperature sensors. Based on the validated modeling framework, the cycle of cure can be optimized by reducing more than half the time of MRCC while obtaining a reliable degree of cure. The shape and size effects of AGS composite structure on the distribution of temperature and degree of cure are also investigated to provide insights for the optimization of soft-mold aided co-curing process.

Optimization of organic solar cells with thin film Au as anode

Optical transmittance and conductivity for thin metallic films, such as Au, are two inversely related and extremely important parameters for its application in organic photovoltaics as the front electrode. We report our findings on how these parameters have been optimized to attain maximum possible efficiencies by fabricating organic solar cells with thin Au film anodes of differing optical transmittances and consequently due to scaling at the nanolevel, varying electrical conductivities. There was an extraordinary improvement in the overall solar cell efficiency (to the order of 49%) when the Au thin film transmittance was increased from 38% to 54%. Surface morphologies of these thin films also have an effect on the critical parameters including, Voc, Jsc and FF.

Biomimicking natural nanopatterned topology by 3D laser lithography

Natural nanopatterned surfaces (nNPS) present on insect wings have demonstrated bactericidal activity [1, 2]. Fabricated nanopatterned surfaces (fNPS) derived by characterization of these wings have also shown superior bactericidal activity [2]. However bactericidal NPS topologies vary in both geometry and chemical characteristics of the individual features in different insects and fabricated surfaces, rendering it difficult to ascertain the optimum geometrical parameters underling bactericidal activity. This situation calls for the adaptation of new and emerging techniques, which are capable of fabricating and characterising comparable structures to nNPS from biocompatible materials. In this research, CAD drawn nNPS representing an area of 10 μm x10 μm was fabricated on a fused silica glass by Nanoscribe photonic professional GT 3D laser lithography system using two photon polymerization lithography. The glass was cleaned with acetone and isopropyl alcohol thrice and a drop of IP-DIP photoresist from Nanoscribe GmbH was cast onto the glass slide prior to patterning. Photosensitive IP-DIP resist was polymerized with high precision to make the surface nanopatterns using a 780 nm wavelength laser. Both moving-beam fixedsample (MBFS) and fixed-beam moving-sample (FBMS) fabrication approaches were tested during the fabrication process to determine the best approach for the precise fabrication of the required nanotopological pattern. Laser power was also optimized to fabricate the required fNPS, where this was changed from 3mW to 10mW to determine the optimum laser power for the polymerization of the photoresist for fabricating FNPS...

Simulated systems optimization through response surface techniques [Optimización de sistemas simulados a través de técnicas de superficie de respuesta]

The purpose of this article is to show the applicability and benefits of the techniques of design of experiments as an optimization tool for discrete simulation models. The simulated systems are computational representations of real-life systems; its characteristics include a constant evolution that follows the occurrence of discrete events along the time. In this study, a production system, designed with the business philosophy JIT (Just in Time) is used, which seeks to achieve excellence in organizations through waste reduction in all the operational aspects. The most typical tool of JIT systems is the KANBAN production control that seeks to synchronize demand with flow of materials, minimize work in process, and define production metrics. Using experimental design techniques for stochastic optimization, the impact of the operational factors on the efficiency of the KANBAN / CONWIP simulation model is analyzed. The results show the effectiveness of the integration of experimental design techniques and discrete simulation models in the calculation of the operational parameters. Furthermore, the reliability of the methodologies found was improved with a new statistical consideration.

The moderating effects of job control and selection, optimization, and compensation strategies on the age-work ability relationship

Work ability describes employees' capability to carry out their work with respect to physical and psychological job demands. This study investigated direct and interactive effects of age, job control, and the use of successful aging strategies called selection, optimization, and compensation (SOC) in predicting work ability. We assessed SOC strategies and job control by using employee self-reports, and we measured employees' work ability using supervisor ratings. Data collected from 173 health-care employees showed that job control was positively associated with work ability. Additionally, we found a three-way interaction effect of age, job control, and use of SOC strategies on work ability. Specifically, the negative relationship between age and work ability was weakest for employees with high job control and high use of SOC strategies. These results suggest that the use of successful aging strategies and enhanced control at work are conducive to maintaining the work ability of aging employees. We discuss theoretical and practical implications regarding the beneficial role of the use of SOC strategies utilized by older employees and enhanced contextual resources at work for aging employees.

The buffering effect of selection, optimization, and compensation strategy use on the relationship between problem solving demands and occupational well-being: A daily diary study

This study investigated within-person relationships between daily problem solving demands, selection, optimization, and compensation (SOC) strategy use, job satisfaction, and fatigue at work. Based on conservation of resources theory, it was hypothesized that high SOC strategy use boosts the positive relationship between problem solving demands and job satisfaction, and buffers the positive relationship between problem solving demands and fatigue. Using a daily diary study design, data were collected from 64 administrative employees who completed a general questionnaire and two daily online questionnaires over four work days. Multilevel analyses showed that problem solving demands were positively related to fatigue, but unrelated to job satisfaction. SOC strategy use was positively related to job satisfaction, but unrelated to fatigue. A buffering effect of high SOC strategy use on the demands-fatigue relationship was found, but no booster effect on the demands-satisfaction relationship. The results suggest that high SOC strategy use is a resource that protects employees from the negative effects of high problem solving demands.

Maintaining a focus on opportunities at work: The interplay between age, job complexity, and the use of selection, optimization, and compensation strategies

The concept of focus on opportunities describes how many new goals, options, and possibilities employees believe to have in their personal future at work. This study investigated the specific and shared effects of age, job complexity, and the use of successful aging strategies called selection, optimization, and compensation (SOC) in predicting focus on opportunities. Results of data collected from 133 employees of one company (mean age = 38 years, SD = 13, range 16–65 years) showed that age was negatively, and job complexity and use of SOC strategies were positively related to focus on opportunities. In addition, older employees in high-complexity jobs and older employees in low-complexity jobs with high use of SOC strategies were better able to maintain a focus on opportunities than older employees in low-complexity jobs with low use of SOC strategies.

Selection, optimization, and compensation strategies: Interactive effects on daily work engagement

The theory of selective optimization with compensation (SOC) proposes that the “orchestrated” use of three distinct action regulation strategies (selection, optimization, and compensation) leads to positive employee outcomes. Previous research examined overall scores and additive models (i.e., main effects) of SOC strategies instead of interaction models in which SOC strategies mutually enhance each other's effects. Thus, a central assumption of SOC theory remains untested. In addition, most research on SOC strategies has been cross-sectional, assuming that employees' use of SOC strategies is stable over time. We conducted a quantitative diary study across nine work days (N = 77; 514 daily entries) to investigate interactive effects of daily SOC strategies on daily work engagement. Results showed that optimization and compensation, but not selection, had positive main effects on work engagement. Moreover, a significant three-way interaction effect indicated that the relationship between selection and work engagement was positive only when both optimization and compensation were high, whereas the relationship was negative when optimization was low and compensation was high. We discuss implications for future research and practice regarding the use of SOC strategies at work.