Special Session: Industry Applications of Business Analytics and Operations Research (IABA&OR)
To remain competitive, firms in almost every industry including customer service, marketing, training, pricing, security, manufacturing and operations, logistics and supply chain management will need not only to adopt Artificial Intelligence (AI) to keep pace with existing peers and digitally native market entrants but also optimization solution development using Operations Research (OR) techniques. On one hand, AI-based approaches enhance performance and greatly reduce workload which depends heavily on historical data, yet many crises rendered near useless in some cases by driving drastic changes in human and market behaviours, making them far from perfect. On the other hand, optimal solutions are always needed to derive in a reasonable time, especially for large-scale problems in the digital era. In this complex and fast-moving environment, traditional approaches to AI and OR need to be strengthened with emerging techniques including bias, fairness, efficiencies, and instability monitoring and modelling. The topics on the trade-offs between performance, quality of solutions, and interpretability as well as new and alternative data for predictive and risk analytics are also crucial to the sustainability of AI-based and OR approaches for Industry applications. This special session is supported by the Vietnam Operations Research Network (VORN). We focus on, but are not limited to the following topics: - Data, Text, and Social Media Mining for Business Analytics
- Case Studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Applications
- Explainable Artificial Intelligence (XAI)
- Operations Research and Machine Learning Applications in Accounting, Finance, Manufacturing and Logistics and Supply Chain Management
- AI-based Advisory in Service-oriented Sectors
- Scheduling, Dynamic Programming, Stochastic Programming, Robust Optimization, Network Flows Optimization, Games Theory
- Data-driven Decision-making in Manufacturing, Management Science, Transportation Science, Engineering, and Organizational Transformation
- Fairness in Algorithmic Decision-Making
- Matheuristics and Metaheuristics in Optimization
- Evolution Programming, Multi-tasking Optimization Applications.
- Machine Learning for Combinatorial Optimization and Optimization for Machine Learning
Paper SubmissionThe papers of this session will be printed in the proceedings of the main conference, which will be published by IEEE and be available at the conference. Papers should be submitted through the online paper submission system: Authors are invited to submit papers of up to 6 pages, written in English, in PDF format and compliant with the IEEE standard. The submissions will be peer-reviewed for originality and scientific quality. Accepted papers will be selected to publish in high-ranked journals in ISI/SCOPUS. Authors of selected papers from the special session will be invited to submit an extended and improved version to a Special Issue published in the Journal of Combinatorial Optimization (SCIE – Q2 – Springer): https://www.springer.com/journal/10878 Session Organizers- Ba-Hung Nguyen (Thai Binh Duong University, Vietnam)
- Su Nguyen (Business School, LaTrobe University, Australia)
- Tai Dinh, (The Kyoto College of Graduate Studies for Informatics)
- Van-Hop Nguyen (School of Industrial Engineering and Management, International University, VNU-HCM)
- Tien Mai (Singapore Management University)
- Trung-Lap Nguyen (Thai Binh Duong University, Vietnam)
Important Dates- Manuscript submission:
June 15, 2022 July 31, 2022 (Extended) - Notification of acceptance:
July 30, 2022 September 06, 2022 (Extended)
Contact- Su Nguyen, Business School, LaTrobe University, Australia (P.Nguyen4@latrobe.edu.au)
- Van-Hop Nguyen, School of Industrial Engineering and Management, International University, VNU-HCM (nvhop@hcmiu.edu.vn)
- Tien Mai, Singapore Management University (atmai@smu.edu.sg)
- Ba-Hung Nguyen, Thai Binh Duong University (hung.nb@tbd.edu.vn)
- Trung-Lap Nguyen, Thai Binh Duong University (lap.nt@tbd.edu.vn)
- Tai Dinh, The Kyoto College of Graduate Studies for Informatics (t_dinh@kcg.edu)
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