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Underground logistics system (ULS) is recognized as sustainable alleviator to road-dominated urban logistics infrastructure with various social and environmental benefits. The purpose of this study is to propose effective modeling and optimization method for planning a hub-and-spoke ULS network in urban region.

Underground freight tunnels and the last-mile ground delivery were organized as a hierarchical network. A mixed-integer programming model (MIP) with minimum system cost was developed. Then a two-phase optimization schema combining Genetic-based fuzzy C-means algorithm (GA-FCM), Depth-first-search FCM (DFS-FCM) algorithm and Dijkstra algorithm (DA), etc. was designed to optimize the location-allocation of ULS facilities and customer clusters. Finally, a real-world simulation was conducted for validation.

The multistage strategy and hybrid algorithms could efficiently yield hub-and-spoke network configurations at the lowest objective cost. GA-FCM performed better than K-means in customer-node clustering. The combination of DFS-FCM and DA achieved superior network configuration than that of combining K-means and minimum spanning tree technique. The results also provided some management insights: (1) greater scale economies effect in underground freight movement could reduce system budget, (2) changes in transportation cost would not have obvious impact on ULS network layout and (3) over 90% of transportation process in ULS network took place underground, giving remarkable alleviation to road freight traffic.

Demand pairs among customers were not considered due to lacking data. Heterogeneity of facilities capacity parameters was omitted.

This study has used an innovative hybrid optimization technique to address the two-phase network planning of urban ULS. The novel design and solution approaches offer insights for urban ULS development and management.

To address the lack of data in this field and determine the relationship between the coefficient of friction and the interference between locomotive wheels and axles, this study evaluates the theoretical relationship between the coefficient of friction and the interference under elastic deformation.

When using numerical analyses to study the mechanical state of the contacting components of the wheels and axle, the interference between the axle parts and the coefficient of friction between the axle parts are two important influencing factors. Currently, as the range of the coefficient of friction between the wheel and axle in interference remains unknown, it is generally considered that the coefficient of friction is only related to the materials of the friction pair; the relationship between the interference and the coefficient of friction is often neglected.

A total of 520 press-fitting experiments were conducted for 130 sets of wheels and axles of the HXD2 locomotive with 4 types of interferences, in order to obtain the relationship between the coefficient of friction between the locomotive wheel and axle and the amount of interference. These results are expected to serve as a reference for selecting the coefficient of friction when designing axle structures with the rolling stock, research on the press-fitting process and evaluations of the fatigue life.

The study provides a basis for the selection of friction coefficient and interference amount in the design of locomotive wheels and axles.

The purpose of this paper is to examine the interaction effect of innovative product category and presentation order on consumer consumer’s purchasing intention and the mediating role of perceived novelty and risk perception.

The authors examined the hypotheses in three experiment studies. In Study 1, the authors primed innovative product category and presentation order on consumer consumer’s purchasing intention. In Study 2, the authors measured the mediating role of perceived novelty and risk perception. In Study 3, they validated the moderating effect of picture and text consistency on the improvement of purchase preference.

The results reveal that RNP/INP and presentation order (from whole to part/from part to whole) could enhance consumers’ purchase intention and verify the mediating role of perceived novelty and risk perception, based on which a complete internal mechanism model is constructed. The third experiment shows the moderating effect of picture and text consistency on the improvement of purchase preference by matching the category and presentation order of innovative products.

Prior literature on the thinking mode of holistic and partial processing has been mostly applied to the cognitive field of reading and text labeling. In this study, using the holistic (local) processing thinking model and anchoring theory, eye movement experiments and situational experiments, the audience’s analysis framework of information processing mechanism is constructed. The unique phenomenon of product category and overall (local) presentation order coexisting in innovative product advertisement is considered comprehensively.

The purpose of this paper is to study the extensive method of grey target based on multi‐stage linguistic label, which is a hypothesis of incomplete information of the weight of stage and decision maker.

For the incomplete weight information case, the weight model for the stage and decision maker is put forward based on the requirement of maximum difference among the alternatives. Also, the weight of the decision maker is estimated by the grey relationship method and the Euclid distance method.

As a result, the method of multiple stage grey target decision making based on linguistic label is suggested. In the incomplete information case, the weight model is suggested and the aggregation is put forward. The suggested method is clear and simple, which can be used in multi‐criteria decision making fields.

This paper offers a very useful result for multi‐attribute decision making.

This paper succeeds in studying the extensive method of grey target based on multi‐stage linguistic label, which is a hypothesis of incomplete information of the weight of stage and the decision maker.

The evaluation scores of each criterion and the integration are given by decision makers, respectively. Owing to the heavy time-pressure in real time decision-making, decision makers may have different judgment abilities, which reflects the instability and inconsistent weight of criteria and scores. It will lead to the unreliable results. To rank alternatives more rational, the consistency of decision makers is considered. The paper aims to discuss these issues.

First, the weight estimation model of the criteria is developed to find the dynamic change and the inconsistency of decision makers, which is based on the objects of weight stability and the consistency measured by the distance between scores of each criterion and the integration. Following that, scores of alternatives given by each decision maker are modified according to the requirement of stability and consistency of the decision-making. In addition, the weight of decision makers is deduced based on the self-consistency and group's similarity that measured by grey close relationship. In the last, the score of alternatives can be modified according to the weight of the decision maker and criteria, and then, alternatives can be ranked via the final score.

The self-adaptation evaluation method is suggested in real time decision-making environment.

Its application step and feasibility is showed via a real decision-making problem.

The purpose of this paper is to present an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

Unlike the convention of developing a set of kinematic equations and then solving them, an alternative numerical algorithm is proposed in which the principal components of link lengths are used as a bridge to analyze the forward kinematics of a Stewart platform. The values of link lengths are firstly transformed to the values of principal components through principal component analysis. Then, the computation of the values of positional variables is transformed to a two‐dimensional nonlinear minimization problem by using the relationships between principal components and positional variables. A hybrid Nelder Mead‐particle swarm optimizer (NM‐PSO) algorithm and a modified NM algorithm are used to solve the two‐dimensional nonlinear minimization problem.

Simulation experiments have been conducted to validate the numerical algorithm and experimental results show that the numerical algorithm is valid and can achieve good accuracy and high efficiency.

This paper proposes an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.

The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.

The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.

Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.

This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.

This paper aims to establish a mathematical model for water-flooding considering the impact of fluid–solid coupling to describe the process of development for a low-permeability reservoir. The numerical simulation method was used to analyze the process of injected water channeling into the interlayer.

Some typical cores including the sandstone and the mudstone were selected to test the permeability and the stress sensitivity, and some curves of the permeability varying with the stress for the cores were obtained to demonstrate the sensitivity of the formation. Based on the experimental results and the software Eclipse and Abaqus, the main injection parameters to reduce the amount of the injected water in flowing into the interlayer were simulated.

The results indicate that the permeability of the mudstone is more sensitive to the stress than sandstone. The injection rate can be as high as possible on the condition that no crack is activated or a new fracture is created in the development. For the B82 block of Daqing oilfield, the suggested pressure of the production pressure should be around 1–3MPa, this pressure must be gradually reached to get a higher efficiency of water injection and avoid damaging the casing.

This work is beneficial to ensure stable production and provide technical support to the production of low permeability reservoirs containing an interlayer.

This study aims to develop an optimal tolerance allocation strategy involves integrating the unique transfer (UT) approach and the difficulty coefficient evaluation (DCE) routine in an interactive hybrid method. This method combines the strengths of both UT and DCE, ensuring simultaneous utilization for enhanced performance. The proposed tolerancing model manifests an integrated computer-aided design (CAD) tool.

By combining UT and DCE based on failure mode, effects and criticality analysis (FMECA) tool and the Ishikawa diagram, the proposed collaborative hybrid tool ensures an efficient and optimal tolerance allocation approach. The integration of these methodologies not only addresses specific transfer challenges through UT but also conducts a thorough evaluation of difficulty coefficients via DCE routine using reliability analysis tools as FMECA tool and the Ishikawa diagram. This comprehensive framework contributes to a robust and informed decision-making process in tolerance allocation, ultimately optimizing the design and manufacturing processes.

The presented methodology is implemented with the aim of generating allocated tolerances that align with specific difficulty requirements, facilitating the creation of a mechanical assembly characterized by high quality and low cost. To substantiate and validate the conceptual framework and methods, an integrated tool has been developed, featuring a graphical user interface (GUI) designed in MATLAB. This interface serves as a platform to showcase various interactive and integrated tolerance allocation approaches that adhere to both functional and manufacturing prerequisites. The proposed integrated tool, designed with a GUI in MATLAB, offers the capability to execute various examples that effectively demonstrate the benefits of the developed tolerance transfer and allocation methodology.

The originality of the proposed approach is the twining between the UT and DCE simultaneous in an integrated and concurrent tolerance transfer and allocation model. Therefore, the proposed approach is named an integrated CAD/tolerance model based on the manufacturing difficulty tool. The obtained results underscore the tangible advantages stemming from the integration of this innovative tolerance transfer and allocation approach. These benefits include a notable reduction in total cost and a concurrent enhancement in product quality.