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Mathematics
Special Issues
Modeling and Optimization in Supply Chain Management
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Modeling and Optimization in Supply Chain Management

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

Deadline for manuscript submissions: 31 March 2026 | Viewed by 1829

Special Issue Editor

Prof. Dr. Rafael Guillermo García-Cáceres

E-Mail Website
Guest Editor
School of Industrial Engineering, Universidad Pedagógica y Tecnológica de Colombia-UPTC, Sogamoso, Colombia
Interests: fuzzy front end; supplier involvement; multicriteria acceptability analysis; fuzzy multi-criteria

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue on “Modelling and Optimization in Supply Chain Management”, to be published in Mathematics. This Special Issue aims to explore contemporary advances in modeling and optimization techniques within supply chain management (SCM). Recognizing the increasing complexity and interconnectedness of modern supply chains, we seek contributions that address both strategic and tactical planning aspects through integrated modeling approaches.

We welcome original research and comprehensive reviews that delve into areas such as multi-echelon inventory systems, demand forecasting, production planning, distribution logistics, and risk management. Emphasis is placed on methodologies that enhance decision support systems, making them more reflective of real-world scenarios.

Submissions employing advanced mathematical models, simulation techniques, and optimization algorithms to solve practical SCM problems are particularly encouraged.

Additionally, studies that incorporate emerging technologies, such as artificial intelligence and machine learning, to improve supply chain resilience and efficiency will be highly regarded.

Through this Special Issue, we aim to bridge the gap between theoretical modeling and practical application, fostering a deeper understanding of how integrated approaches can lead to more robust and adaptable supply chains.

Prof. Dr. Rafael Guillermo García-Cáceres
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 250 words) can be sent to the Editorial Office for assessment.

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

  • supply chain management
  • integrated modeling
  • optimization techniques
  • strategic planning
  • tactical planning
  • decision support systems
  • inventory management
  • production planning
  • distribution logistics
  • risk management
  • simulation
  • artificial intelligence
  • machine learning
  • resilience
  • efficiency

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

40 pages, 4871 KB  
Article
Pricing Optimization for Inventory with Integrated Storage and Credit Constraints
by Hui-Ling Yang, Chun-Tao Chang and Yao-Ting Tseng
Mathematics 2026, 14(1), 163; https://doi.org/10.3390/math14010163 - 31 Dec 2025
Viewed by 178
Abstract
Price is a pivotal determinant of market demand, as higher prices typically reduce sales while lower prices stimulate them. Thus, incorporating price-dependent demand into inventory models is both realistic and necessary. In practice, limited storage capacity often forces retailers to rent additional space, [...] Read more.
Price is a pivotal determinant of market demand, as higher prices typically reduce sales while lower prices stimulate them. Thus, incorporating price-dependent demand into inventory models is both realistic and necessary. In practice, limited storage capacity often forces retailers to rent additional space, motivating the adoption of two-warehouse systems. Trade credit also plays a critical role in supply chain management: suppliers may offer cash discounts or deferred payments to encourage larger orders, while retailers extend credit to customers to boost sales. To reduce default risk, however, retailers usually provide only partial credit. Considering the time value of money, costs and profits are assessed using discounted cash-flow analysis to account for payment delays and inflation. This study develops an integrated supplier–retailer–customer chain model that (1) incorporates price-dependent demand, (2) includes a rented warehouse for limited storage, (3) considers partial trade credit, (4) links two-level trade credit terms to order quantity, and (5) evaluates financial performance on a present-value basis. The model aims to maximize total profit by determining optimal price, replenishment cycle, and order quantity. Numerical and sensitivity analyses confirm that extending supplier credit can lower prices and improve overall profitability, offering useful insights for strategic inventory management. Full article
(This article belongs to the Special Issue Modeling and Optimization in Supply Chain Management)
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31 pages, 1203 KB  
Article
Mathematical Modeling and Optimization of Sustainable Production–Inventory Systems Using Particle Swarm Algorithms
by Chi-Jie Lu, Chih-Te Yang, Dong-Ying Jiang and Ming-Shu Chen
Mathematics 2025, 13(24), 3912; https://doi.org/10.3390/math13243912 - 7 Dec 2025
Viewed by 325
Abstract
This research examines a multinational supply chain inventory problem involving one manufacturer and multiple retailers across a range of carbon emission combinations and an incomplete production system. It aims to identify the optimal strategies for material use, production, delivery, replenishment, and pricing to [...] Read more.
This research examines a multinational supply chain inventory problem involving one manufacturer and multiple retailers across a range of carbon emission combinations and an incomplete production system. It aims to identify the optimal strategies for material use, production, delivery, replenishment, and pricing to maximize the integrated total profits under various situations. Three particle swarm optimization techniques are used to solve all the models. Numerical examples and sensitivity analyses on parameter changes are provided. The findings indicate that in a multinational supply chain, currency appreciation in individual retailers’ countries decreases their optimal order quantities and the manufacturer’s optimal material purchase quantity, but increases the optimal quantity for other retailers. In summary, this study offers valuable guidance to enterprises and supply chain decision-makers, especially those operating in a multinational framework, aiming to effectively balance carbon reduction and profitability within the context of global trends in carbon emission reduction. Full article
(This article belongs to the Special Issue Modeling and Optimization in Supply Chain Management)
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20 pages, 428 KB  
Article
A New Bounding Procedure for Transportation Problems with Stepwise Costs
by Jingyi Liu
Mathematics 2025, 13(22), 3709; https://doi.org/10.3390/math13223709 - 19 Nov 2025
Viewed by 482
Abstract
Transportation planning often involves not only shipment costs but also setup costs associated with deploying vehicles or transport resources. In many practical logistics operations, this setup cost does not remain constant but increases stepwise with the number of vehicles used, reflecting economies of [...] Read more.
Transportation planning often involves not only shipment costs but also setup costs associated with deploying vehicles or transport resources. In many practical logistics operations, this setup cost does not remain constant but increases stepwise with the number of vehicles used, reflecting economies of scale and scheduling thresholds. To capture this realistic feature, this study investigates the transportation problem with stepwise costs, where total costs combine shipment-dependent variable costs and vehicle activation costs. We develop a mixed-integer programming (MIP) model to represent the problem and propose an efficient algorithm based on variable-splitting reformulation and a row-and-column generation scheme. This approach dynamically introduces only the necessary variables and constraints, enabling the solution of large-scale instances that are otherwise computationally challenging. Numerical experiments show that the method produces high-quality solutions much faster than direct MIP solvers. The results highlight the model’s practical value in optimizing fleet utilization and transportation cost structures in real logistics and supply chain systems. Full article
(This article belongs to the Special Issue Modeling and Optimization in Supply Chain Management)
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