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The objective of this paper is to investigate the efficiency of hybrid solution methods when incorporated into large‐scale optimization problems solved by evolution strategies (ESs) and to demonstrate their influence on the overall performance of these optimization algorithms. ESs imitate biological evolution and combine the concept of artificial survival of the fittest with evolutionary operators to form a robust search mechanism. In this paper modified multi‐membered evolution strategies with discrete variables are adopted. Two solution methods are implemented based on the preconditioned conjugate gradient (PCG) algorithm. The first method is a PCG algorithm with a preconditioner resulted from a complete Cholesky factorization, and the second is a PCG algorithm in which a truncated Neumann series expansion is used as a preconditioner. The numerical tests presented demonstrate the computational advantages of the proposed methods, which become more pronounced in large‐scale optimization problems and in a parallel computing environment.

Today's logistics industry is facing severe challenges since global transportation demand increases substantially. Carriers are urged to reduce empty loads and CO2 emissions through collaboration. Therefore, the concept of Physical Internet (PI) came into being. However, PI is still in its infancy. It is difficult to understand its sophisticated coordination mechanism, which makes learning of the concept more complicated.

Gamification is an effective approach to help students improve their learning curve. At the same time, the psychological and behavioral changes in learning will also pose an impact on learning efficiency. This paper introduces a PI transportation game and designs a set of gamification teaching experiments. In the experiment, a control group and three experimental groups are set up, and the experiment was designed to respond to a plethora of research questions using the methods of T-test, correlation analysis and regression analysis. Experimental results were analyzed through the method of multivariate statistics.

This paper looks for superior pedagogical methods and procedures for students to learn PI while providing suggestions for PI's learning among undergraduates. The authors found (1) gamification teaching will make participants feel more satisfied and master more knowledge points; (2) the scores of logistics testing have been significantly improved after gamification teaching and (3) flow experience has a significant impact on game revenue.

This is the first study about the impact of gamification on teaching and learning PI. The authors apply the methods of T-test, correlation analysis and regression analysis to analyze the collected data. The paper proves that gamification can help students learn PI and that flow experience can improve the efficiency of students learning PI.

Promoting low-carbon in the construction industry is important for achieving the overall low-carbon goals. Public–private partnership is very popular in public infrastructure projects. However, different perceptions of low-carbon and behaviors of public and private sectors can hinder the realization of low-carbon in these projects. In order to analyze the willingness of each stakeholder to cooperate towards low-carbon goals, an evolutionary game model is constructed.

An evolutionary game model that considers the opportunistic behavior of the participants is developed. The evolutionary stable strategies (ESSs) under different scenarios are examined, and the factors that influence the willingness to cooperate between the government and private investors are investigated.

The results illustrate that a well-designed system of profit distribution and subsidies can enhance collaboration. Excessive subsidies have negative impact on cooperation between the two sides, because these two sides can weaken income distribution and lead to the free-riding behavior of the government. Under the situation of two ESSs, there is also an optimal revenue distribution coefficient that maximizes the probability of cooperation. With the introduction of supervision and punishment mechanism, the opportunistic behavior of private investors is effectively constrained.

An evolutionary game model is developed to explore the cooperation between the public sector and the private sector in the field of low-carbon construction. Based on the analysis of the model, this paper summarizes the conditions and strategies that can enable the two sectors to cooperate.

Studies on titanium implants have shown that the mechanical properties of the parts are affected by the microstructure characteristic derived from the manufacturing process. The properties of different orientations of specimens under the same process parameters will be different, which should be considered in the application of bone implants. This paper aims to understand the influence of microstructure on micro-hardness, wear and corrosion resistance in different orientations.

The authors manufactured titanium parts and carried out micro-hardness, wear tests and electrochemical corrosion of different orientations under the same process conditions. Then, finally studied the evolution mechanism of the microstructure in different orientations and its influence mechanism on wear and corrosion mechanism.

The melting method makes the grains on the surface in XY orientation finer. The wear mechanism of XY orientation is abrasive wear, that of XZ and YZ orientations are adhesive wear. During corrosion, XY orientation forms a stable passivation film earlier. Compared with XZ and YZ orientations, XY orientation has higher micro-hardness, better wear and corrosion resistance.

In this paper, the microstructure, wear and corrosion resistance of selective laser melted parts were discussed and the differences in different orientations under the same experimental conditions were discussed. The evolution mechanism of the microstructure in different orientations and its influence mechanism on wear mechanism and corrosion mechanism was studied. The mechanical anisotropy of selective laser melted components was discussed.

Merchant guild culture derives from business practices associated with medieval and early modern merchant guilds. This study aims to investigate the nexus between merchant guild culture and firm internationalization as well as the factors that moderate this nexus.

Based on the distribution of the ten merchant guilds in China and data on Chinese listed companies, this study uses the geographical proximity-based method to measure the intensity of merchant guild culture, which is the nearest distance between the ten merchant guilds’ origins and each firm’s registered address.

This study provides robust evidence that merchant guild culture positively relates to the degree of firm internationalization. It also documents that this nexus is stronger for firms with overseas background executives and those situated in highly marketized regions.

The findings of this study have valuable implications for both governments and firms. Governments can leverage local cultures to promote the internationalization of domestic firms, particularly in emerging economies with rich cultural heritage. Firms can further enhance their internationalization efforts by hiring more executives with overseas backgrounds.

This study advances the imprinting literature, provides a novel perspective on the antecedents of firm internationalization and expands research on the contemporary value of historical business culture.

The paper aims to explore how the undue state control leads to the weak stock market in China. It analyzes how the undue state control is exerted in some key areas in the Chinese stock market. This paper intends to expand the existing literature in the relationships among law, politics, and economy.

This paper mainly adopts the exploratory method to analyze the undue state influences. Under some circumstances, comparative study and historical explanation are also adopted.

The paper suggests that to create a strong stock market and facilitate the development of the listed companies and the whole economy, the state should first release its control on the stock market.

Various fields are contained in a stock market, in most of which the undue state control can be observed. In this paper, only some key ones are explored. Further research on other fields and if possible more first‐hand data are necessary.

This paper not only offers an answer to concerns on the various misconducts in the inefficient Chinese stock market and helps to realize the possible ways out of such dilemma, but also it offers implications for other emerging economies.

The on‐going debate on the role of common‐law versus civil‐law system in the capital market may have ignored the state involvement. This paper indicates that it is the undue state control rather than the legal system that leads to the weak stock market in China.

This study aims to study the radar cross-section (RCS) of an intermeshing rotor with blade pitch.

The variation of rotor blade pitch is designed into three modes: fixed mode, linear mode and smooth mode. The dynamic process of two crossed rotors is simulated, where the instantaneous RCS is calculated by physical optics and physical theory of diffraction.

Increasing the pitch angle in the fixed mode can reduce the average RCS of rotor at the given head azimuth. The RCS curve of helicopter in linear mode and smooth mode will have a large peak in the side direction at the given moment. Although the blade pitch in smooth mode is generally larger than that in fixed mode, the smooth mode is conducive to reducing the peak and mean value of helicopter RCS at the given heading azimuth.

The calculation method for analyzing RCS of intermeshing rotor with variable blade pitch is established.

Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate.

First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set.

The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy.

Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study.

In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed.