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Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).

The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.

The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.

This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.

Web-based course assessment is a new thing at China's Open University – China Radio and Television Universities (China RTVUs). This article reports an innovative pilot study in this research area. The experimental course for integrated web-based assessment in this study is Advanced English Writing, which is a compulsory course in the B.A. English programme at China Central Radio and Television University (CCRTVU). The study started in March 2005 and it is still in progress at the moment. This article first describes the webbased assessment design of the course and the implementation procedures. Then it moves on to report some initial feedback from the student participants on the pilot study. The article ends with a tentative plan for further actions based on the current study.

Multiple-source disturbances exist in the polarization sensor, which severely affect the sensor accuracy and stability. Hence, the disturbance analysis plays a vital role in improving the sensor orientation performance. This paper aims to present a novel sensor error model, a disturbances quantitative analysis, a calibration and performance test of polarization sensor based on a polarizing beam splitter.

By combining with the sensor coefficient errors, the Azimuth of Polarization (AoP) error model and the Degree of Polarization (DoP) error model are established, respectively. In addition, the multiple-source disturbances are classified, while the influence on the orientation accuracy is quantitative analyzed. Moreover, the least square optimization algorithm is employed to calibrate the sensor coefficients. Finally, an outdoor test is carried out to test the sensor long-term accuracy.

The theoretical analysis and numerical simulations illustrate that the sensor accuracy is closely related to the disturbances. To eliminate the influence of the disturbances, the least square optimization algorithm, which can minimize the sum of squares of the residual difference of AoP and DoP, is used to calibrate the sensor coefficients. The outdoor test indicates that the sensor can maintain long-term accuracy and stability.

The main contribution of this paper is to establish a novel sensor error model, where the sensor coefficient errors are introduced. In addition, the disturbances are classified and analyzed to evaluate the orientation accuracy of the sensor.

The paper proposes a two-level closed-loop supply chain (CLSC) dynamic competitive model based on different competitive cooperation situations, and explores the impact of competitive cooperation methods on the pricing strategies, recycling and remanufacturing strategies and competitive model selection strategies of supply chain firms.

This paper establishes a CLSC game consisting of a manufacturer and two retailers. Firstly, five CLSC models are established in both horizontal and vertical dimensions, each of which competes with one another. Secondly, the recycling and remanufacturing pricing strategies are analyzed under different competition or cooperation models. Finally, the results are verified through numerical analysis.

The overall profitability of the CLSC is highest when the manufacturer–retailer partnership alliance is in place. The relationship between retailers and manufacturers is also found to be the best way to achieve overall optimization of the CLSC.

The paper investigates the relationship between the competitive partnership and the total profit of the CLSC, taking into account how to optimize the overall benefit, and focusing on how to optimize the individual interests of each participating enterprise. The results can provide basis and guidance for managers' pricing decision and competition cooperation.

To improve power system peak dispatching ability, connecting energy-storage device such as electric vehicle (EV) and regenerative electric heater (REH) to power grid is a good choice.

This paper establishes a multi-energy combined peak dispatching system MCPDS which includes EV, REH and wind power. The matter-element extension model based on improved variable weight theory is applied to evaluate MCPDS synthetic benefit.

The research shows that the MCPDS established in this paper performs excellently in security benefit, economic benefit, social benefit and environmental benefit.

With the assistance of energy storage devices such as EV and REH, the electrical system peak dispatching ability and power system operation efficiency has improved. More devices with energy-storage ability should be introduced into electrical power system to improve its synthetic benefit.

Based on the DVS1608-2011 and IIW-2008 and BS EN15085-3 standards, the stress state grade of welded joints of aluminum alloy EMU (Electric Multiple Units) body was studied.

First, the calculation methods of the stress state grade of aluminum alloy welded joints analyzed by DVS1608-2011 and IIW-2008 standards were studied, and the two methods were programmed by the APDL language of ANSYS. Then, the finite element model of aluminum alloy EMU body was established; the static strength calculation result of the body was compared with the test result, and the error is basically within 10%. Finally, under the acceleration fatigue load provided by BS EN12663 standard, the fatigue analysis was carried out on the welded joint of the vehicle body, and the stress state of the welded joint of the vehicle body was studied according to IIW-2008 and DVS1608 standards, respectively.

The results show that the assessment method based on IIW-2008 standard is more rigorous, and the maximum stress factor of the longitudinal weld between the side beam and the side wall is 0.811; the position occurs in the area where the longitudinal weld of the side beam and the side wall is close to the lower door angle.

The stress state is medium, and the rest of the weld stress states are low.

Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud extraction method that can obtain complete information about the construction of rebar, facilitating construction quality inspection and tunnel data archiving, to reduce the cost and complexity of construction management.

Firstly, this paper analyzes the point cloud data of the tunnel during the construction phase, extracts the main features of the rebar data and proposes an M-E-L recognition method. Secondly, based on the actual conditions of the tunnel and the specifications of Chinese tunnel engineering, a rebar model experiment is designed to obtain experimental data. Finally, the feasibility and accuracy of the M-E-L recognition method are analyzed and tested based on the experimental data from the model.

Based on tunnel morphology characteristics, data preprocessing, Euclidean clustering and PCA shape extraction methods, a M-E-L identification algorithm is proposed for identifying secondary lining rebars in highway tunnel construction stages. The algorithm achieves 100% extraction of the first-layer rebars, allowing for the three-dimensional visualization of the on-site rebar situation. Subsequently, through data processing, rebar dimensions and spacings can be obtained. For the second-layer rebars, 55% extraction is achieved, providing information on the rebar skeleton and partial rebar details at the construction site. These extracted data can be further processed to verify compliance with construction requirements.

This paper introduces a laser point cloud method for double-layer rebar identification in tunnels. Current methods rely heavily on manual detection, lacking objectivity. Objective approaches for automatic rebar identification include image-based and LiDAR-based methods. Image-based methods are constrained by tunnel lighting conditions, while LiDAR focuses on straight rebar skeletons. Our research proposes a 3D point cloud recognition algorithm for tunnel lining rebar. This method can extract double-layer rebars and obtain construction rebar dimensions, enhancing management efficiency.

In this study, superhydrophobic fabric is prepared with a wet-chemical coating technique that uses a coating solution synthesized by the co-hydrolysis and co-condensation of tetraethyl orthosilicate and fluoroalkyl silane (tridecafluorooctyl triethoxysilane) under an alkaline condition. The treated fabric shows stable superhydrophobicity with a water contact angle as high as 171°, and a sliding angle as low as 2°. The coated fabric has higher repellency to saline water, and its repellency increases with increases in the salt content in the solution. The contact angle is reduced with increases in liquid temperature. When the water temperature is 90°C, the contact angle on the superhydrophobic fabric is 153°. The superhydrophobic treatment slightly reduces the air permeability, but increases the water vapor permeability of the fabric. The treatment considerably increases the liquid breakthrough pressure, but has little effect on fabric pore size and thermal conductivity. The air gap membrane distillation process is used to evaluate the desalination performance of the superhydrophobic fabric. When the feed and the condenser are kept at 90°C and 20°C, respectively, the membrane distillation (MD) system with the superhydrophobic fabric yields a permeate flux of water up to 13.8 kg m^-2 hour^-1, which is slightly higher than that with the use of polymer and inorganic MD membranes reported. Superhydrophobic fabrics may thus be considered as effective MD membranes for water desalination applications.

Balancing interfirm relationships is important for firms’ long-term superior performance. However, prior studies mainly focus on interfirm competition or interfirm cooperation separately, ignoring the balance of interfirm relationships. To bridge this gap in knowledge, this study aims to develop a framework to evaluate the balance of interfirm competition and interfirm cooperation and propose strategies to optimize a firm’s interfirm relationships.

After an in-depth literature review, a framework was developed for evaluating and optimizing the interfirm relationships. Taking the high-speed railway industry as an example, the proposed framework was implemented.

The results of the case confirm that the balancing of interfirm relationships can lead to more superior firm performance. Also, rather than mutual suppression, the interfirm competition and interfirm cooperation present a roughly positive relationship.

This study would contribute to the existing knowledge body by developing a framework for balancing interfirm relationships. Also, this study can aid practitioners in evaluating and optimizing their interfirm relationship structures.

Gas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.

In this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.

This paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.

The analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.