Optimizing Logistics Activities: Models and Applications
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Combinatorial Optimization, Graph, and Network Algorithms".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 9
Special Issue Editors
Interests: inventory management; spare parts; supply chain; additive manufacturing; risk assessment
Special Issues, Collections and Topics in MDPI journals
Interests: multi criteria decision making; inventory management; spare parts; additive manufacturing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue of Algorithms aims to gather high-quality contributions in the field of optimization for logistics activities. Logistics operations, such as order picking, vehicle routing, production planning, and related processes, can become extremely costly if not properly optimized.
In recent years, the complexity of these activities has increased significantly due to the following factors:
- The growing flow of products in global supply chains.
- The integration of automation and robotics, requiring real-time decision-making.
- The rise of mass customization, which demands flexible and adaptive processes.
- The exponential growth of e-commerce, leading to high-intensity warehouse operations.
These challenges highlight the urgent need for innovative optimization models capable of addressing new, diverse, and increasingly complex logistics problems. This Special Issue seeks papers that present quantitative approaches applied to real-world logistics challenges. Submissions may focus on, but are not limited to, the following:
- Mathematical optimization models.
- Heuristic and metaheuristic methods.
- Simulation-based optimization.
- Data-driven optimization and AI-based approaches.
- Hybrid decision-support frameworks integrating multiple methods.
Both original research articles and comprehensive review papers are welcome. Review articles should aim to provide a clear overview of the current state of the art and outline promising directions for future research. By bringing together theoretical advancements and practical applications, this Special Issue intends to bridge the gap between academic research and industrial implementation, contributing to more efficient logistics systems.
We look forward to receiving your contributions.
Dr. Antonio Maria Coruzzolo
Dr. Francesco Lolli
Guest Editors
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. Algorithms 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 1800 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 chains
- logistics
- data-driven optimization
- simulation-based optimization
- heuristic and metaheuristic
- hybrid decision-support
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