Algorithmic Design and Optimization in Operations Research and Scheduling

Dear Colleagues,

Operations research (OR) and scheduling serve as the backbone of modern industrial engineering, driving efficiency and innovation across sectors ranging from smart manufacturing to complex service systems. The core challenge in solving problems in this domain lies in designing effective algorithms capable of navigating intricate constraints and vast solution spaces. Recent years have witnessed a paradigm shift driven by the integration of Artificial Intelligence (AI) and Machine Learning (ML), leading to the emergence of powerful, adaptive, and data-driven optimization techniques.

This Special Issue aims to showcase cutting-edge research on algorithmic innovations and their applications in OR and scheduling. We seek original research articles and reviews that push the boundaries of theoretical methodology and practical implementation. Contributions focusing on novel algorithm design, hybrid methodologies, and real-world case studies are particularly encouraged.

Potential topics of interest include, but are not limited to:

1. Learning-Based Optimization Algorithms:​ Integrating AI/ML paradigms such as Deep Reinforcement Learning and surrogate-assisted models to enhance heuristic search capabilities and solve complex combinatorial problems.
2. Multi-Objective Evolutionary Computation:​ Designing Pareto-optimal algorithms for balancing conflicting objectives in scheduling and resource allocation.
3. Hybrid Metaheuristics:​ Developing novel hybrid frameworks combining exact methods with metaheuristics for large-scale optimization.
4. Optimization Under Uncertainty and Robustness:​ Advancing stochastic programming, robust optimization, and distributionally robust approaches for dynamic scheduling and decision-making in volatile environments.
5. Real-World Applications in Smart Manufacturing and Logistics:​ Applying advanced algorithms to address practical challenges in flexible job-shop scheduling and intelligent supply chain management.

We look forward to receiving your valuable contributions to this exciting field.

Prof. Dr. Fajun Yang
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-anonymized 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.