Operational Analytics (Research)
Why it matters?
Operational research involves applying advanced analytical methods to help make better decisions. Originating in the military during World War II, operational research was used to optimize logistics, resource allocation, and strategy, significantly improving wartime operations. For instance, it helped the British military to improve radar detection and the allocation of anti-aircraft artillery, which contributed to the success of Allied forces. Today, operational research is essential for optimizing processes, improving efficiency, and solving complex problems in various industries. Robust operational research solutions provide quantitative insights into operational challenges, supporting strategic planning, resource allocation, and performance improvement. By employing mathematical modeling, statistical analysis, and optimization techniques, operational research helps organizations achieve their objectives and enhance competitiveness.
How we work?
Our company uses Anylogic, Python/R, and GAMS for operational research. Anylogic is a simulation software for modeling complex systems and processes. Python and R offer powerful capabilities for statistical analysis and optimization. GAMS (General Algebraic Modeling System) is a high-level modeling system for mathematical programming and optimization. These tools enable the development of sophisticated models and simulations to address operational challenges.
Sample applications
A notable example of operational research is the optimization of mining operations by Rio Tinto. Using Anylogic and advanced optimization techniques, Rio Tinto can simulate logistics networks, optimize extraction processes, and improve operational efficiency. Another example is in the transport industry, where companies like Delta Airlines use GAMS and Python to optimize flight schedules, crew assignments, and maintenance operations, reducing costs and enhancing service reliability.
Sounds interesting?