Search results

Biogeography‐based optimization algorithm is a new kind of optimization algorithm based on biogeography. It is designed based on the migration strategy of animals to solve the problem of optimization. The purpose of this paper is to present a new algorithm – biogeography migration algorithm for traveling salesman problem (TSPBMA). A new special migration operator is designed for producing new solutions.

The paper gives the definition of TSP and models of TSPBMA; introduces the algorithm of TSPBMA in detail and gives the proof of convergence in theory; provides simulation results of TSPBMA compared with other optimization algorithms for TSP and presents some concluding remarks and suggestions for further work.

The TSPBMA is tested on some classical TSP problems. The comparison results with the other nature‐inspired optimization algorithms show that TSPBMA is useful for TSP combination optimization. Especially, the designed migration operator is very effective for TSP solving. Although the proposed TSPBMA is not better than ant colony algorithm in the respect of convergence speed and accuracy, it provides a new way for this kind of problem.

The migration operator is a new strategy for solving TSPs. It has never been used by any other evolutionary algorithm or swarm intelligence before TSPBMA.

The purpose of this paper is to verify that improved immune network can be used to design new controller for engineering.

First, the definition of artificial immune controller is given out. Second, the disadvantage of Varela immune network which is not fit for control system is pointed out. Third, based on the analysis, the Varela immune network is modified for the purpose of designing controller with the mechanisms of immune network. And an immune controller based on improved Varela immune network (improved Varela immune network model (IVINM)‐AIC) is designed out. Its theoretic background is described in detail.

Based on the theoretic analysis and experiment of motor speed control, it is found that Varela immune work can be used to design immune controller. The experiments results show that IVINM‐AIC is much more robust, stable and anti‐delay and less overshoot than classical proportion, integration, and differentiation controller. It is good at controlling nonlinear system which is single input single output (SISO) system. The limitation of IVINM‐AIC is that it is used for simple SISO system.

The theoretic analysis of improved Varela immune network controller is original and it is useful for the analysis and design of new and complex immune controller. The experiment design is useful for comparison of new test in future.

The purpose of this paper is to examine how advertising is used by real estate companies as an instrument for managing the adverse effects of a catastrophe.

Through a theoretical analysis, types of post-disaster advertising messages were identified. On the basis of the likely variations in post-disaster advertising, a content analysis was conducted of a sample of 4,150 property print advertisements to identify advertising messages related to the earthquake. Finally, the message changes in these earthquake-related advertisements were evaluated and compared with the dimension of time to explore the development of advertising strategies.

The authors found that 12 types of advertising messages were used by developers in response to the Wenchuan earthquake. The initial advertising strategy was mainly to manage public relations, then the strategy was to reduce or compensate for the increased earthquake risk perceptions of buyers.

The findings provide valuable references for helping enterprises adopt effective advertising messages and strategies to reduce the negative effects of disasters.

There are only a few studies on advertising campaigns, especially in the real estate industry, that have been conducted in the wake of catastrophes. This study sought to expand upon the scarce findings in this particular field.

Based on upper echelons theory and social contagion theory, we investigate how environmental leadership affects GIC via green human resource management (GHRM) and examine the moderating role of environmental climate.

We conduct hierarchical regression and use the bootstrap method to analyze the two-waved data from 317 Chinese manufacturers in order to verify the hypotheses.

The results indicate that GHRM mediates the impacts of environmental leadership on green human capital, structural capital and relational capital. In addition, environmental climate strengthens the positive impact of environmental leadership on GHRM.

Our study enriches the literature on GIC by uncovering the “black box” between environmental leadership and GIC, providing a logical framework opposite to mainstream GIC research, and expanding the boundary condition for GIC accumulation. This study provides more logical paths for enterprises and governments to increase the accumulation of GIC and promote green intellectual economy development.

This study aims to manufacture cotton fabric with thermal regulation performance by using the composite phase change material (CPCM) prepared by coating paraffin doped with expanded graphite (EG), and the thermal effect of the fabric material was evaluated and characterized.

EG/paraffin CPCM with shape stability and enhanced thermal conductivity were prepared by the impregnation method and then finished on the surface of cotton fabric with coating technology. The microstructure, crystal structure, chemical composition, latent heat property and thermal conductivity were analyzed by scanning electron microscope, x-ray diffraction, Fourier transform infrared spectroscopy, differential scanning calorimeter and thermal constant analyzer. The photo-thermal effect of the coated fabric was studied by a thermal infrared imager.

CPCM prepared with a mass ratio of EG to paraffin of 1:8 showed excellent shape stability and low paraffin leakage rate. The latent heat of the CPCM was 51.6201 J/g and the thermal conductivity coefficient was increased by 11.4 times compared with the mixed paraffin. After the CPCM was coated on the surface of the cotton fabric, the light-to-heat conversion rate of the C-EG/PA3 sample was improved by 86.32% compared with the original fabric. In addition, the coated fabric showed excellent thermal stability and heat storage performance in the thermal cycling test.

EG can improve the shape stability and thermal conductivity of paraffin but will reduce the latent heat energy.

The method developed provided a simple and practical solution to improving the thermal regulation performance of fabrics.

Combining paraffin wax with fabrics in a composite way is innovative and has certain applicability in improving the thermal properties of fabrics.

This study explores the antecedent configurations shaping ambidextrous environmental strategy (AES) and the subsequent performance outcomes. The lack of literature from the configurational perspective and inconsistent performance results suggest that this study has significant implications for practitioners, policymakers and the public. Therefore, this study aims to investigate how different antecedent conditions interact to shape AES and subsequent performance outcomes.

To achieve the research aims, the current research utilize research techniques based on technology–organization–environment framework and configurational perspective. This study collects data from 317 Chinese manufacturing enterprises and tests the theoretical framework using fuzzy set qualitative comparative analysis and propensity score matching.

Perceived institutional pressure, green supply chain integration and digital technology adoption form four paths that lead to the existence of AES. There are four sets of replaceable conditions between distinct paths. In addition, except for configuration P3, all other configurations promote environmental, operational and financial performance.

Our results provide new insights for enterprises to shape AES and achieve multiple performances, and new ideas for promoting environmental policies and public environmental awareness.

This study adds literature on AES and confirms multiple drivers, revealing their interaction mechanisms and key antecedent conditions. In addition, this study promotes the performance practice of AES by examining different AES configurations that achieve triple performance and insignificant operational performance.

In some three-dimensional (3D) printing application scenarios, e.g., model manufacture, it is necessary to print large-sized objects. However, it is impossible to implement large-size 3D printing using a single projector in digital light processing (DLP)-based mask projection 3D printing because of the limitations of the digital micromirror device chips.

A multi-projector DLP with energy homogenization (EHMP-DLP) scheme is proposed for large-size 3D printing. First, a large-area printing plane is established by tiling multiple projectors. Second, the projector set’s tiling pattern is obtained automatically, and the maximum printable plane is determined. Third, the energy is homogenized across the entire printable plane by adjusting gray levels of the images input into the projectors. Finally, slices are automatically segmented based on the tiling pattern of the projector set, and the gray levels of these slices are reassigned based on the images of the corresponding projectors.

Large-area high-intensity projection for mask projection 3D printing can be performed by tiling multiple DLP projectors. The tiled projector output energies can be homogenized by adjusting the images of the projectors. Uniform ultraviolet energy is important for high-quality printing.

A prototype device is constructed using two projectors. The printable area becomes 140 × 210 mm from the original 140 × 110 mm.

The proposed EHMP-DLP scheme enables 3D printing of large-size objects with linearly increasing printing times and high printing precision. A device was established using two projectors to practice the scheme and can easily be extended to larger sizes by using more projectors.

The pressure sensors can convert external pressure or mechanical deformation into electrical power and signal, which cannot only detect pressure or strain changes but also harvest energy as a self-powered sensor. This study aims to develop a self-powered flexible pressure sensor based on regular nanopatterned polymer films.

In this paper, the self-powered flexible pressure sensor is mainly composed of two nanopatterned polymer films and one conductive electrode layer between them, which is a sandwich structure. The regular nanostructures increase the film roughness and contact area to enhance the friction effect. To enhance the performance of the pressure sensor, different nanostructures on soft polymer sensitive layers are fabricated using UV nanoimprint lithography to generate more triboelectric charges.

Finally, the self-powered flexible pressure sensor is prepared, which consists of sub-200 nm resolution regular nanostructures on the surface of the elastic layer and an indium tin oxide electrode thin film. By converting the friction mechanical energy into electrical power, a maximum power of 423.8 mW/m2 and the sensitivity of 0.8 V/kPa at a frequency of 5 Hz are obtained, which proves the excellent sensing performance of the sensor.

The acquired electrical power and pressure signal by the sensor would be processed in the signal process circuit, which is capable of immediately and sustainably driving the highly integrated self-powered sensor system. Results of the experiments show that this new pressure sensor is a potential method for personal pressure monitoring, featured as being wearable, cost-effective, non-invasive and user-friendly.

This study/paper aims to reach the core objective of hospitality order cancellation prediction (HOCP), that is, to identify potential cancellers from many customer bases, thereby enhancing the effectiveness of customer retention campaigns. However, few studies have focused on predicting hospitality order cancellation.

A novel profit-driven model for predicting hospitality order cancellation is proposed to bridge this research gap. The authors construct profit-driven extreme gradient boosting (XGBoost) based on a grid search on HOCP to maximize profit by selecting optimal hyperparameters of XGBoost.

Real-world data set is analyzed, and the proposed model yields more profits than other predictive models. Sensitivity analysis proves that the proposed model is robust to the key hyperparameter and application scenario. Furthermore, some preventive measures based on visual analysis results are provided to reduce the cancelled probability of orders.

This research will help hotel managers to transfer the modeling goal to profit orientation and encourage relevant researchers to interpret the prediction results of models for hotel order cancellation prediction in a post hoc manner. Besides, the proposed model can be applied to various enterprises with different average order profits and help managers optimize revenue management.

This research expands the relevant literature and offers guidance for predicting hospitality order cancellation from a profit-driven perspective at the customer level. The proposed model can provide macro-control to hotel managers and obtain the most satisfactory profits in micro-control.