Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Journal Citation Indicator0.400
Impact Factor1.305

Decisions and Coordination of Dual-Channel Supply Chain considering Retailers’ Bidirectional Fairness Concerns under Carbon Tax Policy

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Mathematical Problems in Engineering is a broad-based journal publishing results of rigorous engineering research across all disciplines, carried out using mathematical tools.

 Editor spotlight

Chief Editor, Professor Guangming Xie, is currently a full professor of dynamics and control with the College of Engineering, Peking University. His research interests include complex system dynamics and control and intelligent and biomimetic robots.

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks

Computational intelligence methods play an important role for supporting smart networks operations, optimization, and management. In wireless sensor networks (WSNs), increasing the number of nodes has a need for transferring large volume of data to remote nodes without any loss. These large amounts of data transmission might lead to exceeding the capacity of WSNs, which results in congestion, latency, and packet loss. Congestion in WSNs not only results in information loss but also burns a significant amount of energy. To tackle this issue, a practical computational intelligence approach for optimizing data transmission while decreasing latency is necessary. In this article, a Softmax-Regressed-Tanimoto-Reweight-Boost-Classification- (SRTRBC-) based machine learning technique is proposed for effective routing in WSNs. It can route packets around busy locations by selecting nodes with higher energy and lower load. The proposed SRTRBC technique is composed of two steps: route path construction and congestion-aware MIMO routing. Prior to constructing the route path, the residual energy of the node is determined. After that, the residual energy level is analyzed using softmax regression to determine whether or not the node is energy efficient. The energy-efficient nodes are located, and numerous paths between the source and sink nodes are established using route request and route reply. Following that, the SRTRBC technique is used for congestion-aware routing based on buffer space and bandwidth capability. The path that requires the least buffer space and has the highest bandwidth capacity is picked as the optimal route path among multiple paths. Finally, congestion-aware data transmission is used to minimize latency and data loss along the route path. The simulation considers a variety of performance metrics, including energy consumption, data delivery rate, data loss rate, throughput, and delay, in relation to the amount of data packets and sensor nodes.

Research Article

How Does Media Coverage of Entrepreneurship Affect Entrepreneurial Decision-Making of Returning Migrant Workers in China? A Moderated Mediation Model

As an important measure to help returning migrant workers (RMWs) to make entrepreneurial decisions, media coverage received much attention in recent years in China. In this study, we take the hierarchical regression method to examine how media coverage of entrepreneurship (MCE) affects the entrepreneurial intention (EI) and entrepreneurial decision-making (ED) of RMWs. The results prove that MCE has a significant positive effect on EI and ED of RMWs and that the entrepreneurial knowledge (EK) negatively moderates the relationship between MCE and EI of RMWs and positively moderates the mediating effect of EI. Meanwhile, we also find that risk propensity (RP) of RMWs plays a positive role in the above-mentioned relationship. The obtained results enlighten us on the fact that we should not only pay attention to the agenda-setting effect of the media coverage but also carry out differentiated MCE for RMWs with different EKs and RP.

Research Article

A Continuous Test Method for Dynamic Change of Real Mesostructures of Soil

The regularity of dynamic change of real mesostructures of soil is the foundation of the macro- and mesointegrated research. Mesoscale research about continuous image acquisition in real soils, identifying and quantifying mesostructures, is the subject of current interest. Soil mesostructure measurement method is the basis of modeling, and the development of rapid, direct, and lower-cost methods has great practical value for engineering practice. Combined with conventional triaxial loading test equipment, optical measurement, mesoscopic imaging tracking system, and digital image technology, a new method for measuring the dynamic change of the soil mesostructure is designed. This integrated approach to observation and acquisition is realized by direct observation and continuous image capture for dynamic change of real mesostructures of soil. The methods are used to analyze the high compressibility of a certain clay, shear zone development of cement soil, and erosive effects of ecological soil in order to investigate the continuous variation of mesostructures during the shear test. The aim of this paper is to provide a simple, straightforward, continuous, and low-cost test method for revealing the characteristics of consecutive change of real mesostructures of soil in the conventional triaxial test.

Research Article

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

To prevent traffic congestion, drivers always adjust the driving behavior with their driving information. By considering the self-anticipation effect and the optimal current difference effect on traffic flow stability, a novel two-lane lattice hydrodynamic model is proposed. Compared with Peng’s model, the linear stability analysis results reveal that the self-anticipation term can effectively enlarge the stable region on the phase diagram. Then, a reductive perturbation method is used to derive the mKdV equation describing traffic congestion near the critical point. Nonlinear analyses show that the traffic congestions can be effectively suppressed by taking the coefficient of lane-changing behaviors and the anticipation time into account. These results further indicate that the driver’s self-anticipation current difference effect can efficiently alleviate traffic jams. Furthermore, the numerical simulations with periodic boundary conditions also confirm the effectiveness of theoretical results.

Research Article

Einstein-Ordered Weighted Geometric Operator for Pythagorean Fuzzy Soft Set with Its Application to Solve MAGDM Problem

The Pythagorean fuzzy soft set (PFSS) is the most influential and operative tool for maneuvering compared to the Pythagorean fuzzy set (PFS), which can accommodate the parameterization of alternatives. It is also a generalized form of intuitionistic fuzzy soft sets (IFSS), which delivers healthier and more exact valuations in the decision-making (DM) procedure. The primary purpose is to extend and propose ideas related to Einstein’s ordered weighted geometric aggregation operator from fuzzy structure to PFSS structure. The core objective of this work is to present a PFSS aggregation operator, such as the Pythagorean fuzzy soft Einstein-ordered weighted geometric (PFSEOWG) operator. In addition, the basic properties of the proposed operator are introduced, such as idempotency, boundedness, and homogeneity. Moreover, a DM method based on a developed operator has been presented to solve the multiattribute group decision-making (MAGDM) problem. A real-life application of the anticipated method has been offered for a capitalist to choose the most delicate business to finance his money. Finally, a brief comparative analysis with some current methods demonstrates the proposed approach’s effectiveness and reliability.

Research Article

Pricing Strategies of Dual-Recycling Channels considering Refurbishing and Remanufacturing of WEEE

This article studies pricing strategies of the dual-channel recycling supply chain where the manufacturer and the recycler compete on price in recycling waste electrical and electronic equipment (WEEE) and cooperate in disposing of them. This article is based on whether the recycler can refurbish and distinguish two different treatment methods of WEEE: refurbishment by the recycler and remanufacturing by the manufacturer. Two dual-channel recycling structures are proposed: (1) the recycler cannot refurbish when the manufacturer remanufactures; (2) the recycler can refurbish when the manufacturer remanufactures. By solving two Stackelberg game models, we derive pricing strategies. The impacts of recycled products’ quality and base profit for remanufacturing and refurbishing on pricing strategies are discussed. We find that the recycler prefers refurbishing when its base profit for refurbishment is greater than the manufacturer’s base profit for remanufacturing, rather than the transfer price. Interestingly, the recycler’s refurbishment does not reduce the manufacturer’s profits but creates a win-win situation through their cooperation. Furthermore, the better quality of recycled products and the higher base profit for refurbishing and remanufacturing can bring more profit to the recycler and the manufacturer, increase the recycling prices, improve the efficiency of resource utilization, and reduce environmental pollution.

Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Journal Citation Indicator0.400
Impact Factor1.305
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.