Aims and scope

Advances in Operation Research and Production Management (AORPM) is an open-access, peer-reviewed academic journal hosted by Center of Management Case Studies, Beijing University of Technology and published by EWA Publishing. AORPM present latest theoretical and methodological discussions to bear on the scholarly works covering operation, applied mathematics and project management. Situated at the forefront of the interdisciplinary fields of operation research and production management, this journal seeks to bring together the scholarly insights centering on management, statistics, mathematical analysis, artificial intelligence and relevant subfields that trace to the discipline of operation, production management, project management, and combined fields of the aforementioned. AORPM is dedicated to the gathering of intellectual views by scholars and policymakers. The articles included are relevant for scholars, policymakers, and students of operation, management, and otherwise interdisciplinary programs.

AORPM has a collaborative "journal-author-reviewer" system (JAR System) to provide maximum support to authors during the reviewing process. The editorial team is committed to promptly addressing the progress of submitted manuscripts. AORPM is devoted to upholding high standards and efficiency as its core principles, with the primary objective of enhancing the user experience for all kinds of authors. AORPM sincerely invites and welcomes scholars from around the world to share their research accomplishments. In its endeavour to promote global academic equity and contribute to disciplinary advancement, AORPM extends additional support and fee waivers to researchers from third-world countries, as well as underdeveloped regions. Manuscripts that are suitable for publication in the AORPM cover domains on various perspectives of engineering and their impacts on individuals, businesses and society. Subject areas include, but are not limited to:

Operation Research

Reliability Engineering

Management Science & Engineering

• Management
• Project Management

Mathematical Sciences & Statistics

• Applied Mathematics
• Data Science
• Foundations of Mathematical Science
• Applied Statistics

Industrial Engineering

• Standardization Engineering
• Quality Management Engineering

Logistical Management & Engineering

• Logistical Management
• Logistical Engineering

Artificial Intelligence

• Multi-factor decision