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In real-world cases, it is common to encounter mixed discrete-continuous problems where some or all of the variables may take only discrete values. To solve these non-linear optimization problems, the use of finite element methods is very time-consuming. The purpose of this study is to investigate the efficiency of the proposed hybrid algorithms for the mixed discrete-continuous optimization and compare it with the performance of genetic algorithms (GAs).

In this paper, the enhanced multipoint approximation method (MAM) is used to reduce the original nonlinear optimization problem to a sequence of approximations. Then, the sequential quadratic programing technique is applied to find the continuous solution. Following that, the implementation of discrete capability into the MAM is developed to solve the mixed discrete-continuous optimization problems.

The efficiency and rate of convergence of the developed hybrid algorithms outperforming GA are examined by six detailed case studies in the ten-bar planar truss problem, and the superiority of the Hooke–Jeeves assisted MAM algorithm over the other two hybrid algorithms and GAs is concluded.

The authors propose three efficient hybrid algorithms, the rounding-off, the coordinate search and the Hooke–Jeeves search-assisted MAMs, to solve nonlinear mixed discrete-continuous optimization problems. Implementations include the development of new procedures for sampling discrete points, the modification of the trust region adaptation strategy and strategies for solving mix optimization problems. To improve the efficiency and effectiveness of metamodel construction, regressors f defined in this paper can have the form in common with the empirical formulation of the problems in many engineering subjects.

Although supply chain collaboration (SCC) theoretically boosts the adoption of supply chain finance (SCF) through information sharing and cost savings, many companies with good supply chain partnerships still hesitate to engage in SCF. To disentangle this puzzle, this study aims to explore how two dimensions of information transparency (i.e. information quantity and information quality) and two types of transaction dependence (i.e. dependence on suppliers and dependence on customers) influence the relationship between SCC and SCF adoption.

This study uses secondary survey data from a Chinese bank, including 464 Chinese companies that have adopted SCF to varying degrees. This study then performs the logistic regression analysis to test the hypotheses.

This study empirically confirms that SCC shows a positive relationship with SCF adoption. More interestingly, information quantity negatively moderates this positive relationship, whereas information quality positively moderates this positive relationship. Most surprisingly, dependence on customers rather than dependence on suppliers strengthens this positive relationship.

This study makes theoretical contributions to the SCF literature by demonstrating the distinct moderating mechanisms regarding the relationship between SCC and SCF adoption. The findings also help companies reexamine their interactions with supply chain members.

Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in knowledge sharing area, and knowledge payment is one of the most effective ways to achieve it. Therefore, the knowledge payment has been regarded as a huge business opportunity, and it is of great meaning to study the development trend and feasibility of knowledge payment. This chapter, through big data methods, analyzes the business model of Zhihu (a Chinese platform of knowledge sharing) after it introduced knowledge payment projects, such as Zhihu Live and Pay Consultation. According to data of Zhihu users’ Q&A, concerned fields and others, this chapter tries to outline its user profile to find out the target groups of different topics, the proper form of knowledge payment and the hot topics of Zhihu Live. Through the analysis of knowledge graph, this chapter finds that Zhihu Live is expected to be the mainstream knowledge payment form in the future, and the most potential topics are mainly focused on science, law, and business. Meanwhile, it establishes a pricing model for Zhihu Live, and provides suggestions for the development of knowledge payment.

This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point.

Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%–41% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability.

An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

In this paper, we model histories of coresidence between two cohorts of urban Chinese couples, married during the Cultural Revolution and early market reform periods. Most research on coresidence pictures families cross‐sectionally, but nuclear households are a natural part of extended coresidence systems that prefer stem family arrangements. We study histories of coresidence to determine what predicts ever having coresided with the husband’s parents, comparing the predictive power of modernization theory to the impact of demographic change, the availability of household members, and the resources and needs of each generation. While married children’s needs for childcare do not propel them into coresidence, they strongly predict the likelihood of staying coresident.

Drawing upon psychological ownership theory, the aim of this study was to uncover the coexisting mediating effects of knowledge sharing and hiding on the relationship between employees’ organizational psychological ownership (OPO) and their innovative work behavior (IWB). The moderating role of organizational context in these mediating relationships was further examined to determine the moderated mediation paths.

This study mainly used a survey-based research method and collected data from 512 professionals from both public and private organizations in Pakistan to test our proposed hypotheses.

The results showed that coexisting knowledge sharing and hiding mediated the relationship between employees’ OPO and IWB. Furthermore, organizational context moderated the mediated relationships, providing support for the moderated mediation framework.

The results highlight the significance of fostering employees’ OPO to enhance their IWB by promoting knowledge sharing and preventing knowledge hiding. This study also urges managers to consider the contingency effect of organizational contexts when promoting employees’ IWB in emerging economies.

The results obtained in this study suggest that the knowledge behavior paradox occurs in organizations, and distinct organizational contexts play crucial but differential roles in intervening in the effect of employees’ OPO on their IWB. This study empirically validated this complex mechanism in an important emerging economy in Asia.

This study aims to solve the premature failure of the rubber stator due to wear, reduce the frictional resistance moment of the screw pump to solve the problem of a model of Daqing oilfield screw pump oil recovery system shutdown after the difficult start.

For the first time, the rotor surface of a screw pump was treated with dot-matrix texture to study the effect of dot matrix texture on the tribological performance of the stator-rotor friction subsets of screw pump. Reciprocating friction tests with different texture morphologies (S-shape, double tongue) and angular parameters (0°, 45° and 90°) were conducted at 10% of the texture area and pump silicone grease.

When point texture was added to the surface of the rotor sample, the friction coefficient and wear quantity of the sample were lower than those of the surface without texture treatment, and the double tongue 0° combination showed the best tribological properties. At this time, the average coefficient of friction and wear is reduced by 22.8% and 62%, 28.6% and 64.8%.

The introduction of texture can effectively improve the tribological performance of progressive screw pumps, and this paper provides important theoretical and experimental support for the design of progressive screw pumps in practical applications.

Blockchain is a technical solution integrating multiple technologies, with the potential to overcome the drawbacks of organizational governance. Given the emergence and prevalence of blockchain, its importance for organizational governance has progressively increased. Therefore, this study aims to analyze how blockchain restructure organizational governance.

This study presents a structured systematic literature review of blockchain-enabled applications across diverse organizational governance models and several case studies to illustrate them. Based on the above analysis, governance mechanisms, transaction upgrading and challenges are proposed.

Based on the literature review and typical applications, the authors summarize the advances in the research on the theoretical and practical applications of blockchain in organizational governance. We also identify the influence mechanisms of organizational governance and investigate transaction upgrading based on blockchain. Finally, the authors discuss three types of challenges (i.e. administrative, technical and environmental) to the relationship between blockchain and organizational governance. Along with the development of blockchain applications, the impact of blockchain on organizational governance has progressed in both theory and practice. Therefore, these findings will have significant implications for both academics and practitioners.

This paper makes three key theoretical contributions: we review the literature on the impact of blockchain on organizational governance and present typical cases to illustrate it; propose four governance mechanisms for the application of blockchain in organizational governance; and propose an innovating-and-matching-oriented model of transaction upgrading based on blockchain.