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Recent Advances in Sustainability and Supply Chain Management: Mathematical Modelling,...
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Recent Advances in Sustainability and Supply Chain Management: Mathematical Modelling, Optimization and Applications

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3608

Special Issue Editor

Dr. Songsong Liu

E-Mail Website
Guest Editor
School of Management, Harbin Institute of Technology, Harbin 150001, China
Interests: complex system modeling, optimization, and decision making; supply chain optimization; low carbon and sustainability management and optimization; data mining and analytics; engineering optimization

Special Issue Information

Dear Colleagues,

Sustainability factors have been key considerations in recent literature on supply chain management to promote information and capital flow and establish highly efficient, reliable, and competitive supply chains with characteristics including but not limited to economic profitability, low carbon emissions, and social fairness. Mathematical-optimization-based methodologies have been widely applied to obtain sustainable supply chains with significantly successful outcomes in various areas and industrial/business sectors. Novel and advanced mathematical models, algorithms, approaches, and tools have strong theoretical and application potentials and research opportunities for sustainability and supply chain management, which attract strong interest from academia and industry.

This Special Issue of Mathematics focusing on the topic of “Recent Advances in Sustainability and Supply Chain Management: Mathematical Modeling, Optimization, and Applications” aims to address the major sustainability concerns of supply chain management in this era of smart technologies, such as big data, machine learning, artificial intelligence, and blockchain, and collect state-of-the-art research works on the development and applications of novel mathematical models, algorithms, approaches, and tools for supply chain management to achieve supply chain sustainability. Interdisciplinary works across a range of fields, such as management, economics, engineering, health, are particularly welcome.

Dr. Songsong Liu
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

  • supply chain
  • sustainability
  • optimization
  • mathematical model
  • carbon neutrality
  • social fairness
  • big data
  • machine learning
  • artificial intelligence
  • blockchain

Published Papers (2 papers)

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Research

23 pages, 1705 KiB  
Article
Multi-Stage Production and Process Outsourcing in Automobile-Part Supply Chain Considering a Carbon Tax Strategy Using Sequential Quadratic Optimization Technique
by Mohammed Alkahtani, Lofti Hidri and Mehdi Mrad
Mathematics 2023, 11(5), 1191; https://doi.org/10.3390/math11051191 - 28 Feb 2023
Cited by 1 | Viewed by 1289
Abstract
This research focused on modeling and optimizing production and outsourcing operations in a supply chain (SC) while considering environmental challenges. The proposed mathematical model was nonlinear, implying outsourcing, and took into account reworking and carbon tax. It was solved using sequential quadratic programming [...] Read more.
This research focused on modeling and optimizing production and outsourcing operations in a supply chain (SC) while considering environmental challenges. The proposed mathematical model was nonlinear, implying outsourcing, and took into account reworking and carbon tax. It was solved using sequential quadratic programming (SQP) to achieve best solutions. Transportation significantly impacts carbon emission, which, herein, was considered the total cost of the SC. The model was tested using data from the automobile part industry, and sensitivity analyses were performed to understand the impacts of individual parameters on the total cost of the supply chain. The results could provide valuable insights for managers seeking to optimize production and outsourcing for a resilient supply chain. Full article
(This article belongs to the Special Issue Recent Advances in Sustainability and Supply Chain Management: Mathematical Modelling, Optimization and Applications)
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41 pages, 4299 KiB  
Article
An Inventory Model in a Three-Echelon Supply Chain for Growing Items with Imperfect Quality, Mortality, and Shortages under Carbon Emissions When the Demand Is Price Sensitive
by Cynthia Griselle De-la-Cruz-Márquez, Leopoldo Eduardo Cárdenas-Barrón, Buddhadev Mandal, Neale R. Smith, Rafael Ernesto Bourguet-Díaz, Imelda de Jesús Loera-Hernández, Armando Céspedes-Mota and Gerardo Treviño-Garza
Mathematics 2022, 10(24), 4684; https://doi.org/10.3390/math10244684 - 10 Dec 2022
Cited by 7 | Viewed by 1575
Abstract
This research develops an optimization model for growing items in a supply chain with three stages: farmer, processor, and retailer while considering imperfect quality, mortality, shortages with full backordering, and carbon emissions. In the farmer stage, during the growing period, not all articles [...] Read more.
This research develops an optimization model for growing items in a supply chain with three stages: farmer, processor, and retailer while considering imperfect quality, mortality, shortages with full backordering, and carbon emissions. In the farmer stage, during the growing period, not all articles survive until the end of the period, so a density function of the probability of survival and death of the growing articles is taken into account. Moreover, it is considered imperfect quality in the retailer’s stage because as the supply chain goes down, there exists a greater probability of product defects. Here, the end customer (consumer) can detect poor-quality aspects such as poorly cut, poorly packed, expired products, etc. An inventory model that maximizes the expected total profit is formulated for a single type of growing items with price-dependent polynomial demand. An algorithm is developed to solve the optimization problem generating the optimal solution for order quantity, backordering quantity, selling price, and the number of shipments that maximizes the expected total profit per unit of time, and a numerical example is used to describe the applicability of the proposed inventory model. Finally, a sensitivity analysis has been carried out for all the input parameters of the inventory model, where the effect of each of the parameters on the decision variables is shown to extract some management knowledge. It was found that holding costs in the three stages of the supply chain have a substantial impact on the total profit per unit of time. In addition, as the demand scale parameter increases, the company must raise the selling price, which directly impacts the expected total profit per unit of time. This inventory model has the advantage that it can be applied to any growing item, including animals or plants, so it helps the owners of farms or crops to generate the most significant possible profit with their existing resources. Full article
(This article belongs to the Special Issue Recent Advances in Sustainability and Supply Chain Management: Mathematical Modelling, Optimization and Applications)
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