Some Applications of Mathematical Methodologies in Operations Research

Dear Colleagues,

The applications of mathematical methods for operations research are well established. The emerging field of operations research includes factors and issues such as technology evolvement in inventory management, flexible production, smart production, work-in-process inventory management through advanced technology, advanced manufacturing with automation, climate change, and sustainability under supply chain management with the aim of sustainable development goals (SDGs). In other words, operations research emerges with the SDGs. The emerging fields require mathematical methods such as calculus, statistics, probability, queuing theory, and numerical methods along with developed metaheuristics and advanced artificial intelligence for problem solving and decision making. This Special Issue aims to find novel mathematical methods for optimization and problem solving in the emerging fields of operations research, especially for technology development, sustainability, and climate change issues within operations research. The proposed methods should solve higher-dimensional non-linear constraint and unconstraint optimization problems, but should not be limited to these. Novel approaches for complex linear constraints and unconstraint problems are also acceptable. Authors can submit original research and review articles, empirical studies and case studies, and short notes on mathematical methods for the above-mentioned topics. All theory, concept, and data-driven original methods are welcome to be submitted. Articles will be chosen based on the merit and feasibility of the application scope of the methods in the field of operations research. The scope of this Special Issue is not only limited to the above topics of operations research but also welcomes other novel methods for problem solving, global optimization, and best-fit solutions.

Dr. Rekha Guchhait
Prof. Dr. Biswajit Sarkar
Guest Editors

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• mathematical modelling
• proabability and statistical methods
• constraint and unconstraint optimization
• linear and non-linear optimization
• algorithm development for optimization
• metaheuristic optimization in operations research
• machine learning application in advanced operations research
• artificial intelligence in mathematical methods
• decision support system for advanced operations research problems
• mathematical methods for supply chain management
• sustainable development goals