Cutting-Edge Datasets and Algorithms for Enhancing Industrial Processes and Supply Chain Optimization

Dear Colleagues,

This Special Issue focuses on the latest advancements in the use of cutting-edge datasets and algorithms to optimize industrial processes and supply chain management. It aims to bring together researchers and practitioners to share insights, methodologies, and case studies that demonstrate the transformative potential of data-driven approaches in these fields. The issue will explore how innovative data utilization and algorithmic strategies can enhance efficiency, reduce costs, and improve overall performance in industrial and supply chain operations.

Potential topics:

• Advanced Datasets for Industrial Applications;
• Data preprocessing and integration techniques;
• Case studies on the use of datasets in manufacturing and supply chains;  
• Machine learning and AI algorithms for industrial processes;
• Optimization algorithms for supply chain management;
• Predictive maintenance and quality control algorithm;
• Modeling and analysis of stochastic processes;
• Applications of stochastic optimization in production planning;
• Risk management and uncertainty in supply chain;
• End-to-end supply chain optimization strategies;
• Inventory management and demand forecasting;
• Logistics and transportation optimization;  
• Successful implementations of data-driven strategies.

This Special Issue invites original research papers, reviews, and case studies that provide new insights and practical solutions for enhancing industrial and supply chain process optimization through the use of advanced datasets and algorithms.

Prof. Dr. Iván Pérez-Olguín
Dr. Luis Carlos Méndez González
Prof. Dr. Luis Alberto Rodríguez-Picón
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 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. Data 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 1600 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.