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Mathematics
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Theoretical and Applied Mathematics in Supply Chain Management
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Theoretical and Applied Mathematics in Supply Chain Management

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

Deadline for manuscript submissions: 30 April 2024 | Viewed by 2399

Special Issue Editor

Dr. Xiang Song

E-Mail Website
Guest Editor
School of Mathematics and Physics, University of Portsmouth, Portsmouth PO1 3HF, UK
Interests: logistics and transportation; supply chain management; cutting and packing

Special Issue Information

Dear Colleagues,

Theoretical and applied mathematics play a crucial role in supply chain management. Supply chain management involves the coordination of the flow of goods, services, and information from raw materials to finished products delivered to customers. Theoretical and applied mathematics provide the core tools for supply chain modelling and optimisation. Specific areas of mathematics commonly used in supply chain management include linear programming, stochastic programming, goal programming, data envelopment analysis, queuing theory, game theory, graph theory, statistics, probability, machine learning, and more. For example, mathematical models are developed to represent the flow of goods and services in a supply chain. These models can identify bottlenecks, reduce inventory and transportation costs, increase efficiency, and improve customer service. More complicated maths, such as calculus, stochastic models, and queuing theories, is applied to help with inventory management.  

In this Special Issue, we encourage submissions providing new contributions at the theoretical level as well as in terms of applications, to provide directions in which novel ideas might be applied in the context of supply chain management. Potential topics include, but are not limited to, the following:

  1. LARG—lean, agile, resilient, and green;
  2. Supply chain modelling and optimization;
  3. Demand forecasting;
  4. Inventory management;
  5. Logistics and transportation;
  6. Reverse and closed-loop supply chains;
  7. Supply chain coordination.

Dr. Xiang Song
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.

Keywords

  • LARG—lean, agile, resilient, and green
  • supply chain modelling and optimization
  • demand forecasting
  • inventory management
  • logistics and transportation
  • reverse and closed-loop supply chains
  • supply chain coordination

Published Papers (3 papers)

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Research

30 pages, 1760 KiB  
Article
Shortage Policies for a Jump Process with Positive and Negative Batch Arrivals in a Random Environment
by Yonit Barron
Mathematics 2024, 12(9), 1341; https://doi.org/10.3390/math12091341 - 28 Apr 2024
Viewed by 143
Abstract
We study a continuous-review stock management of a retailer for a single item in a limited storage (buffer) in a random environment. The stock level fluctuates according to two independent compound Poisson processes with discrete amounts of items (batches) that enter and leave [...] Read more.
We study a continuous-review stock management of a retailer for a single item in a limited storage (buffer) in a random environment. The stock level fluctuates according to two independent compound Poisson processes with discrete amounts of items (batches) that enter and leave the storage facility. The storage facility is controlled by a three-parameter base-stock replenishment policy. All items exceeding the storage capacity are transferred to an unlimited foreign facility. In addition, a restricted backlogging possibility is permitted; additional demands for items are lost sales. We further assume a random shelf life, the possibility of total inventory collapse, and a random lead time. Applying Markov theory, we derive the optimal control parameters minimizing the long-run expected total cost. A sensitivity analysis is conducted focusing on the comparison between the pure lost-sales policy and a partial backordering policy. Accordingly, we identify cases where one policy is cost effective compared to the other, particularly with respect to the batch patterns (sign, rate, average, and variability), and the associated costs. Full article
(This article belongs to the Special Issue Theoretical and Applied Mathematics in Supply Chain Management)
20 pages, 2157 KiB  
Article
The Emission Reduction Technology Decision of the Port Supply Chain
by Yan Zhou and Haiying Zhou
Mathematics 2024, 12(6), 848; https://doi.org/10.3390/math12060848 - 14 Mar 2024
Viewed by 497
Abstract
The technology options for sustainable development are explored with customer low-carbon preference in a port supply chain consisting of one ship and one port. Port supply chains can opt for either shower power or low-sulfur fuel oil to cut down emissions. We set [...] Read more.
The technology options for sustainable development are explored with customer low-carbon preference in a port supply chain consisting of one ship and one port. Port supply chains can opt for either shower power or low-sulfur fuel oil to cut down emissions. We set game models considering three power structures: the port dominant (port-led Stackelberg game), the ship dominant (ship-led Stackelberg game), and the port and ship on the same footing (Nash game). We compare the performances of different technologies. It is shown that, when customer low-carbon preference and carbon tax are both low, LSFO is the appropriate choice from the supply chain’s profit perspective, SP is preferred from the emission control perspective, and LSFO is preferred from the social welfare perspective. However, when customers’ low-carbon preferences, carbon tax, and environmental concerns are all low or all high, LSFO should be adopted from the view of social welfare. The profits and carbon emissions of the supply chain in the Nash game are higher than those in the Stackelberg game. While the environmental concern is low, the social welfare of the supply chain in the Nash game is greater than that in the Stackelberg game. Otherwise, it is less than that in the Stackelberg game. The obtained results can help governments formulate policies and ships make emission reduction technology decisions according to their own interests. Full article
(This article belongs to the Special Issue Theoretical and Applied Mathematics in Supply Chain Management)
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21 pages, 2423 KiB  
Article
A Cost Optimisation Model for Maintenance Planning in Offshore Wind Farms with Wind Speed Dependent Failure Rates
by Xiaodong Li, Xiang Song and Djamila Ouelhadj
Mathematics 2023, 11(13), 2809; https://doi.org/10.3390/math11132809 - 22 Jun 2023
Cited by 1 | Viewed by 1032
Abstract
This paper presents an optimisation model for cost optimisation of maintenance at an offshore wind farm (OWF). The model is created for OWF project developers to optimise strategic resources to meet their maintenance demand. The model takes into account various maintenance categories on [...] Read more.
This paper presents an optimisation model for cost optimisation of maintenance at an offshore wind farm (OWF). The model is created for OWF project developers to optimise strategic resources to meet their maintenance demand. The model takes into account various maintenance categories on a full range of wind turbine components; the failure rate associated with each component is dependent on wind speed in order to consider weather uncertainty. Weibull distribution is used to predict the probability of wind speed occurring during a given period based on available historical data. The performance of the proposed optimisation model has been validated using reference cases and a UK OWF in operation. Various optimal solutions are investigated for the problems with increased and decreased mean turbine failure rates as a sensitivity test of the model. Full article
(This article belongs to the Special Issue Theoretical and Applied Mathematics in Supply Chain Management)
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