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Mathematics
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Applied Mathematics in Supply Chain and Logistics
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Applied Mathematics in Supply Chain and Logistics

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 6130

Special Issue Editor

Prof. Dr. Chunqiao Tan

E-Mail Website
Guest Editor
School of Business, Central South University, Yuelu District, Changsha 410083, China
Interests: game theory and application; decision analysis; supply chain and logistics management; business big data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The function of supply chain management is to design and manage the processes, assets, and flows of material and information required to satisfy customers’ demands. The globalization of the economy and electronic commerce has heightened the strategic importance of supply chain management. E-logistics has created new distribution channels for consumers. The last decade has seen rapid growth in business models built around digital platforms that bring together buyers and sellers to interact and trade in new and innovative ways. These business models, referred to as the sharing economy, on-demand economy, and platform economy, bring new challenges to supply chain management and logistics. The COVID-19 pandemic has profoundly affected the stability of global logistics and supply chains. Rapid advances and complexity in digital technology, such as big data, cloud computing, blockchain, and artificial intelligence (AI), as well as the growing uncertainty in the global business environment, have had a profound impact on the development of supply chain management and logistics. The global economy and advanced digital technologies have also generated unprecedented opportunities for innovative methodologies and technologies for designing, operating, and managing supply chains and logistics.

This Special Issue aims to collate original research papers that offer the latest developments and applications of supply chain management and logistics in a broad range of fields.

  • sustainable supply chain;
  • green supply chain;
  • low-carbon supply chain;
  • closed-loop supply chain;
  • omni-channel supply chain;
  • low-carbon logistics;
  • supply chain agility;
  • supply chain adaptability;
  • dynamic supply chain alignment;
  • supply chain resilience;
  • mathematical logistics;
  • game theory;
  • contract design;
  • information economy;
  • marketing;
  • big data;
  • blockchain;
  • artificial intelligence;
  • platform economy;
  • on-demand economy;
  • sharing economy;
  • digital economy;
  • multiple-criteria decision-making.

Prof. Dr. Chunqiao Tan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (8 papers)

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Research

19 pages, 2594 KiB  
Article
Recycling Models of Waste Electrical and Electronic Equipment under Market-Driven Deposit-Refund System: A Stackelberg Game Analysis
by Yi Liu, Weihua Liu and Chunsheng Li
Mathematics 2024, 12(14), 2187; https://doi.org/10.3390/math12142187 - 12 Jul 2024
Viewed by 375
Abstract
Recycling waste electrical and electronic equipment (WEEE) has garnered considerable societal attention. To incentivize WEEE recycling within a closed-loop supply chain (CLSC), a deposit-refund system (DRS) has been implemented. This study delves into the implications of a market-driven DRS on WEEE recycling under [...] Read more.
Recycling waste electrical and electronic equipment (WEEE) has garnered considerable societal attention. To incentivize WEEE recycling within a closed-loop supply chain (CLSC), a deposit-refund system (DRS) has been implemented. This study delves into the implications of a market-driven DRS on WEEE recycling under different recycling models. A Stackelberg game analysis is employed, where an electronics manufacturer (leader) has sufficient channel power over an electronics retailer and a third-party recycler (followers). The results indicate that the market-driven DRS significantly incentivizes consumer recycling efforts, ultimately elevating the economic efficiency of the supply chain. When the electronics manufacturer assumes responsibility for WEEE recycling, it streamlines the recycling process, thereby enhancing operational efficiency and profitability. Conversely, when the electronics retailer handles WEEE recycling, it reduces retail prices and simplifies the recycling process, positively influencing consumer purchasing behavior. However, when a third-party recycler undertakes WEEE recycling, the recycling volume tends to be minimal, resulting in the lowest level of supply chain profits. This paper provides theoretical and practical implications for improving the recycling effectiveness and operational efficiency of the CLSC. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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12 pages, 1086 KiB  
Article
Rightful Rewards: Refining Equity in Team Resource Allocation through a Data-Driven Optimization Approach
by Bo Jiang, Xuecheng Tian, King-Wah Pang, Qixiu Cheng, Yong Jin and Shuaian Wang
Mathematics 2024, 12(13), 2095; https://doi.org/10.3390/math12132095 - 3 Jul 2024
Viewed by 427
Abstract
In group management, accurate assessment of individual performance is crucial for the fair allocation of resources such as bonuses. This paper explores the complexities of gauging each participant’s contribution in multi-participant projects, particularly through the lens of self-reporting—a method fraught with the challenges [...] Read more.
In group management, accurate assessment of individual performance is crucial for the fair allocation of resources such as bonuses. This paper explores the complexities of gauging each participant’s contribution in multi-participant projects, particularly through the lens of self-reporting—a method fraught with the challenges of under-reporting and over-reporting, which can skew resource allocation and undermine fairness. Addressing the limitations of current assessment methods, which often rely solely on self-reported data, this study proposes a novel equitable allocation policy that accounts for inherent biases in self-reporting. By developing a data-driven mathematical optimization model, we aim to more accurately align resource allocation with actual contributions, thus enhancing team efficiency and cohesion. Our computational experiments validate the proposed model’s effectiveness in achieving a more equitable allocation of resources, suggesting significant implications for management practices in team settings. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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13 pages, 5661 KiB  
Article
Mixed-Integer Optimization for Ship Retrofitting in Green Logistics
by Tianfang Ma, Xuecheng Tian, Yan Liu, Yong Jin and Shuaian Wang
Mathematics 2024, 12(12), 1831; https://doi.org/10.3390/math12121831 - 12 Jun 2024
Viewed by 375
Abstract
Maritime transportation plays a pivotal role in global trade and international supply chains. However, the sector is also a significant source of emissions. One of the most promising technologies for reducing these emissions is air lubrication, which involves installing bubbles along the hull [...] Read more.
Maritime transportation plays a pivotal role in global trade and international supply chains. However, the sector is also a significant source of emissions. One of the most promising technologies for reducing these emissions is air lubrication, which involves installing bubbles along the hull of a ship. Despite its potential, the design of cost-effective bubble-installation plans for ship fleets over the planning horizon remains unexplored in the literature. This paper addresses this gap by proposing a mathematical programming model designed to optimize the installation of bubble-based systems. We present several propositions concerning the model’s properties, supported by rigorous proofs. To validate the model’s effectiveness, we conduct a series of computational experiments. The findings demonstrate that our optimization model enables shipping companies to devise bubble-installation plans that are cost-effective. This contribution not only extends the current understanding of emission reduction technologies in maritime transportation, but also offers practical insights for their implementation. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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23 pages, 903 KiB  
Article
Optimal Routing and Scheduling of Flag State Control Officers in Maritime Transportation
by Xizi Qiao, Ying Yang, Yu Guo, Yong Jin and Shuaian Wang
Mathematics 2024, 12(11), 1647; https://doi.org/10.3390/math12111647 - 24 May 2024
Viewed by 511
Abstract
Maritime transportation plays a pivotal role in the global merchandise trade. To improve maritime safety and protect the environment, every state must effectively control ships flying its flag, which is called flag state control (FSC). However, the existing FSC system is so inefficient [...] Read more.
Maritime transportation plays a pivotal role in the global merchandise trade. To improve maritime safety and protect the environment, every state must effectively control ships flying its flag, which is called flag state control (FSC). However, the existing FSC system is so inefficient that it cannot perform its intended function. In this study, we adopt an optimization method to tackle this problem by constructing an integer programming (IP) model to solve the FSC officer routing and scheduling problem, which aims to maximize the total weight of inspected ships with limited budget and human resources. Then we prove that the IP model can be reformulated into a partially relaxed IP model with the guarantee of the result optimality. Finally, we perform a case study using the Hong Kong port as an example. The results show that our model can be solved to optimality within one second at different scales of the problem, with the ship number ranging from 20 to 1000. Furthermore, our study can be extended by considering the arrangement of working timetables with finer granularity and the fatigue level of personnel. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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23 pages, 6223 KiB  
Article
Research on Dynamic Takeout Delivery Vehicle Routing Problem under Time-Varying Subdivision Road Network
by Fengjie Xie, Zhiting Chen and Zhuan Zhang
Mathematics 2024, 12(7), 962; https://doi.org/10.3390/math12070962 - 24 Mar 2024
Cited by 1 | Viewed by 886
Abstract
For the dynamic takeout delivery vehicle routing problem, which faces fluctuating order demand and time-varying speeds, this study presents a novel approach. We analyze the time distribution of takeout orders and apply a Receding Horizon Control (RHC) strategy to convert the dynamic challenge [...] Read more.
For the dynamic takeout delivery vehicle routing problem, which faces fluctuating order demand and time-varying speeds, this study presents a novel approach. We analyze the time distribution of takeout orders and apply a Receding Horizon Control (RHC) strategy to convert the dynamic challenge into a static one. The driving speed of delivery vehicles on different roads at different times is determined based on the subdivision criteria of the urban road network and a traffic congestion measurement method. We propose a dynamic takeout delivery vehicle routing optimization model and a time-varying subdivision road network is established to minimize the total delivery cost. We validated the model through simulation examples. The optimization results show that the total distribution cost is reduced after considering the time-varying subdivision road network, with the penalty cost decreasing by 39%. It is evident that considering the subdivision of the road network can enhance order delivery efficiency and optimize the overall dining experience. The sensitivity analysis of various parameters reveals that the delivery platform must appropriately determine the time domain and allocate the number of delivery personnel based on order scale to avoid escalating delivery costs. These findings provide theoretical guidance for vehicle routing planning in the context of delivery platforms. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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24 pages, 6000 KiB  
Article
Usefulness of the Ordinal Logistic Biplot: Analysis of the Path Taken towards a Circular Primary Sector in Spain
by Saudi-Yulieth Enciso-Alfaro, Víctor Amor-Esteban, Davi-Jônatas Cunha-Araújo and Isabel-María García-Sánchez
Mathematics 2024, 12(2), 322; https://doi.org/10.3390/math12020322 - 18 Jan 2024
Viewed by 1037
Abstract
Population growth and greater global interconnection require a profound transformation in how we produce, consume, and manage natural resources. In this sense, the circular transition of the agricultural and livestock sectors is vital to guarantee adequate production without compromising the availability of resources [...] Read more.
Population growth and greater global interconnection require a profound transformation in how we produce, consume, and manage natural resources. In this sense, the circular transition of the agricultural and livestock sectors is vital to guarantee adequate production without compromising the availability of resources for future generations. In this work, we analyze the level of circular development of the primary sector in Spain using a sample of the 84 largest companies. We utilize the biplot analysis, multivariate graphic models that represent the joint distribution of four scores (constructed with sixteen ecological initiatives), and three financial and geographic variables. These techniques allow for visualization of the status and the relationships between all of them. We evidence an important degree of progress in initiatives associated with the use of non-polluting energy, eco-design, eco-innovation, management, and care of ecosystems. We also observe that the current transition towards a circular primary sector is strongly associated with firms’ capital investments and long-term innovations. On the other hand, the actions aimed at protecting water resources are in an intermediate state of progress, being necessary to invest in additional friendly water initiatives. In this vein, it is advisable to promote public policies focused on promoting the ecological transition of this sector and the research that advances efficient water management. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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20 pages, 1972 KiB  
Article
Recycling Pricing and Government Subsidy Strategy for End-of-Life Vehicles in a Reverse Supply Chain under Consumer Recycling Channel Preferences
by Zhiguo Wang
Mathematics 2024, 12(1), 35; https://doi.org/10.3390/math12010035 - 22 Dec 2023
Cited by 1 | Viewed by 1015
Abstract
In the existing recycling system for end-of-life vehicles (ELVs), online recycling based on the Internet platform is a useful supplement. In this paper, a Stackelberg game pricing model, which is dominated by ELV part remanufacturers and composed of remanufacturers, recyclers, and consumers, is [...] Read more.
In the existing recycling system for end-of-life vehicles (ELVs), online recycling based on the Internet platform is a useful supplement. In this paper, a Stackelberg game pricing model, which is dominated by ELV part remanufacturers and composed of remanufacturers, recyclers, and consumers, is constructed considering consumer preferences for recycling channels. The influence of different subsidy strategies on the optimal pricing, profit, and recycling volume of the reverse supply chain (RSC) of ELVs is discussed, and the effects of factors such as subsidy amount and consumer preferences on the RSC of ELVs are analyzed using numerical simulation. The results show that the increase in consumers’ online recycling preferences has a positive effect on the recycling volume and profit of the RSC of ELVs. Considering the recycling volume of the RSC, when fewer subsidies are given, more recycling volume can be generated by subsidizing remanufacturers, and, on the contrary, recycling volume will be generated by subsidizing consumers. Considering the profit of the RSC, when subsidies are given at the lower-middle level, higher profits can be earned by subsidizing remanufacturers, and, on the contrary, higher profits can be earned by subsidizing consumers. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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15 pages, 4026 KiB  
Article
On the Fundamental Diagram for Freeway Traffic: Exploring the Lower Bound of the Fitting Error and Correcting the Generalized Linear Regression Models
by Yidan Shangguan, Xuecheng Tian, Sheng Jin, Kun Gao, Xiaosong Hu, Wen Yi, Yu Guo and Shuaian Wang
Mathematics 2023, 11(16), 3460; https://doi.org/10.3390/math11163460 - 9 Aug 2023
Viewed by 936
Abstract
In traffic flow, the relationship between speed and density exhibits decreasing monotonicity and continuity, which is characterized by various models such as the Greenshields and Greenberg models. However, some existing models, i.e., the Underwood and Northwestern models, introduce bias by incorrectly utilizing linear [...] Read more.
In traffic flow, the relationship between speed and density exhibits decreasing monotonicity and continuity, which is characterized by various models such as the Greenshields and Greenberg models. However, some existing models, i.e., the Underwood and Northwestern models, introduce bias by incorrectly utilizing linear regression for parameter calibration. Furthermore, the lower bound of the fitting errors for all these models remains unknown. To address above issues, this study first proves the bias associated with using linear regression in handling the Underwood and Northwestern models and corrects it, resulting in a significantly lower mean squared error (MSE). Second, a quadratic programming model is developed to obtain the lower bound of the MSE for these existing models. The relative gaps between the MSEs of existing models and the lower bound indicate that the existing models still have a lot of potential for improvement. Full article
(This article belongs to the Special Issue Applied Mathematics in Supply Chain and Logistics)
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