Operations Research and Management Science (ORM)

Section Information

Operations Research and Management Science focuses on the development and application of analytical, mathematical, and computational methods to support decision-making, optimize processes, and improve organizational performance. It examines how systems operate, how resources can be allocated efficiently, and how complex problems can be modeled and solved across industries.

Modern research in this field includes optimization theory, stochastic modeling, simulation, supply chain management, logistics, operations strategy, decision analysis, scheduling, data-driven optimization, and the integration of AI and machine learning into operations research methods. Advances in algorithms, computing power, and real-time analytics continue to expand the scope of ORM.

This section publishes theoretical studies, applied models, empirical analyses, simulations, reviews, and case studies addressing optimization, operational efficiency, planning, forecasting, and management strategies that enhance decision-making in business, engineering, healthcare, transportation, and public systems.

Scope

Optimization Theory and Methods
- Linear, nonlinear, integer, and mixed-integer optimization
- Convex and combinatorial optimization
- Heuristics, metaheuristics, and evolutionary algorithms
- Applications in engineering, logistics, and resource allocation
Stochastic Models and Uncertainty Analysis
- Stochastic processes, queuing models, and Markov chains
- Risk analysis, reliability, and probabilistic modeling
- Decision-making under uncertainty and stochastic optimization
- Applications in finance, healthcare, and service systems
Simulation and Computational Modeling
- Discrete-event simulation, Monte Carlo methods, and system dynamics
- Agent-based modeling and complex systems analysis
- Simulation–optimization integration and digital twins
- Performance evaluation for large-scale systems
Supply Chain Management and Logistics
- Supply chain design, coordination, and risk management
- Inventory control, warehousing, and distribution strategies
- Transportation planning, routing, and network optimization
- Global logistics, sustainability, and resilience
Operations Management and Strategy
- Process design, capacity planning, and productivity improvement
- Lean operations, quality management, and performance metrics
- Project management, scheduling, and resource allocation
- Operations strategy in manufacturing and service systems
Decision Analysis and Multi-Criteria Methods
- Decision trees, utility theory, and preference modeling
- Multi-criteria decision-making (MCDM) techniques
- Risk preferences, behavioral decision-making, and judgment
- Applications in policy, environmental planning, and finance
Data Analytics, Machine Learning, and OR Integration
- Predictive analytics and statistical learning for decision support
- Optimization-informed machine learning and hybrid models
- Big data methods and real-time analytics for operations
- AI applications in forecasting, planning, and automation
Applications in Engineering, Healthcare, and Public Systems
- Healthcare operations, scheduling, and resource allocation
- Transportation systems, energy networks, and infrastructure planning
- Emergency response, public safety, and disaster management
- Industrial engineering, manufacturing optimization, and service design