Operations research
Operations research is an applied discipline that uses mathematical and analytical methods to support decision-making and improve operations under constraints.
Statistics Slam Dunk
Operations research is the analytical discipline of using mathematical models and optimization methods to support decisions under constraints.
- How it is used
- Supports NBA roster and strategy decisions by replacing guesswork with mathematical models and optimization.
- How deep it goes
- Demonstrates constrained optimization through objectives, hard constraints, lpSolve, and an interpreted roster result, while surveying other techniques.
- Examples
- Uses a 24-player free-agent pool, five-position roster, $90 million salary cap, and 30-year average-age limit.
- What you can do after
- Apply it via lpSolve to select an optimal free-agent roster under linear, continuous constraints.
Read how Statistics Slam Dunk explains operations research →
The AI Pocket Book
A discipline that applies mathematical methods to make better decisions under constraints, often for business optimization.
- How it is used
- Positions operations research as a business-facing technical specialty for solving constrained decisions.
- How deep it goes
- Explains the role of optimization and goal-mapping, but stops short of formal methods or algorithm details.
- Examples
- Uses inventory allocation to warehouses from a demand forecast as the concrete example.
- What you can do after
- Apply it to turn business goals into optimization problems and choose workable decisions under constraints.
Related concepts
- optimizationincludes · Optimization is the systematic selection or adjustment of values, actions, or system designs to improve a specified objective, often subject to constraints.
- machine learninguses · Machine learning is a field of computational methods in which systems learn patterns or relationships from data to make predictions, decisions, or other outputs.
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