Sustainable Logistics Systems: The Impacts of Artificial Intelligence and Combinatorial Optimization
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: 22 July 2026 | Viewed by 33
Special Issue Editors
Interests: optimization; simulation; AI; supply chain; project management
Special Issues, Collections and Topics in MDPI journals
Interests: optimization; simulation; AI; supply chain; project management
Special Issue Information
Dear Colleagues,
The Special Issue examines how AI and optimization techniques can drive sustainability in modern supply chains, and how, by leveraging artificial intelligence (AI) and combinatorial optimization, logistics systems can achieve greater efficiency while reducing environmental harm. Key applications include carbon-aware vehicle routing, machine-learning decision support, and digital twins in logistics, which optimize operations to minimize fuel consumption and emissions. Metaheuristic algorithms further enhance solutions for complex problems like load balancing and reverse logistics, supporting circular economy principles.
Additionally, green supply chain management and lifecycle carbon footprint reduction are critical themes, emphasizing how AI-driven analytics and optimization contribute to sustainable resource use. These technologies enable smarter inventory management, waste reduction, and energy-efficient transportation, aligning logistics with global sustainability goals. By integrating AI and optimization, businesses can build resilient, low-carbon supply chains, demonstrating that technological innovation and environmental responsibility can go hand in hand. This research provides actionable insights that will contribute to the achievement of eco-friendly logistics in an era of climate urgency.
We welcome original research articles and reviews that advance the sustainable logistics agenda through artificial intelligence or combinatorial optimization (or the synergy thereof). Submissions may explore, but are not limited to, the following topics:
- Carbon-aware vehicle routing, fleet electrification, and charging scheduling models;
- AI-enhanced heuristics for multi-modal or stochastic logistics networks;
- Data-driven digital twins, predictive maintenance, and resilient warehousing;
- Lifecycle-integrated optimization incorporating social impact or circular economy objectives;
- Policy analyses and real-world pilots demonstrating measurable sustainability gains.
Prof. Dr. Sameh Al-Shihabi
Dr. Mohammad AlDurgam
Dr. Dua Weraikat
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. Sustainability 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 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
- sustainable logistics
- artificial intelligence
- combinatorial optimization
- green supply chain management
- carbon-aware vehicle routing
- metaheuristic algorithms
- machine-learning decision support
- digital twins in logistics
- reverse and circular logistics
- lifecycle carbon footprint reduction
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