Operations Research in Optimization of Supply Chain Management

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Supply Chain Management".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1193

Special Issue Editor


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Guest Editor
Industrial and Manufacturing Engineering Department, Kettering University, Flint, MI 48504, USA
Interests: applied optimization; operations management; logistics and supply chain management; sustainable manufacturing systems; statistical data analysis; energy planning; engineering education
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Special Issue Information

Dear Colleagues,

We invite submissions to the Special Issue entitled “Operations Research in Optimization of Supply Chain Management”. The increasing complexity of supply chain systems necessitate innovative approaches to their modeling, analysis, and optimization. This Special Issue seeks high-quality contributions that apply operations research to model and optimize supply chains across strategic, tactical, and operational levels.

We particularly welcome work that not only addresses classical challenges—such as inventory management, logistics, location planning, and network design—but also explores emerging topics, including sustainability, digital transformation, AI/ML integration, agility, resilience under disruption, and decentralized decision making. We encourage both methodological advances and real-world applications that contribute to the understanding and optimization of modern supply chains. In addition, general and systematic literature reviews that map existing research and highlight emerging trends are also welcome.

Dr. Farnaz Ghazi-Nezami
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. Systems is an international peer-reviewed open access monthly 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 2400 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

  • operations research
  • supply chain optimization
  • mathematical modeling
  • logistics and transportation

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Published Papers (1 paper)

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15 pages, 2204 KB  
Article
Resolving Conflicting Goals in Manufacturing Supply Chains: A Deterministic Multi-Objective Approach
by Selman Karagoz
Systems 2026, 14(2), 126; https://doi.org/10.3390/systems14020126 - 27 Jan 2026
Viewed by 257
Abstract
In the context of manufacturing logistics, this study sheds light on the difficult task of concurrently optimizing cost, time, influence on sustainability, and spatial efficiency. Specifically, this addresses the integrated challenge of material handling equipment selection and facility space allocation, a crucial decision-making [...] Read more.
In the context of manufacturing logistics, this study sheds light on the difficult task of concurrently optimizing cost, time, influence on sustainability, and spatial efficiency. Specifically, this addresses the integrated challenge of material handling equipment selection and facility space allocation, a crucial decision-making domain where conventional single-objective methodologies frequently overlook vital considerations. While recent research predominantly relies on meta-heuristics and simulation-based solution methodologies, they do not guarantee a global optimum solution space. To effectively address this multifaceted decision environment, a Mixed-Integer Linear Programming (MILP) model is developed and resolved utilizing two distinct scalarization methodologies: the conventional ϵ-constraint method and the augmented ϵ-constraint method (AUGMECON2). The comparative analysis indicates that although both methods effectively identify the Pareto front, the AUGMECON2 approach offers a more robust assurance of solution efficiency by incorporating slack variables. The results illustrate a convex trade-off between capital expenditure and operational flow time, indicating that substantial reductions in time necessitate strategic investments in higher-capacity equipment fleets. Furthermore, the analysis underscores a significant conflict between achieving extreme operational efficiency and adhering to facility design standards, as reducing time or energy consumption beyond a specific point requires deviations from optimal space allocation policies. Ultimately, a “Best Compromise Solution” is determined that harmonizes near-optimal operational efficiency with strict compliance to spatial constraints, providing a resilient framework for sustainable manufacturing logistical planning. Full article
(This article belongs to the Special Issue Operations Research in Optimization of Supply Chain Management)
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