OR POST study guide
OR POST · Work through your exam, one topic at a time.
The OR POST is a professional certification examination in operations research. It is designed for analysts, engineers, data scientists, and graduate students who apply quantitative methods to decision problems in industry, government, or consulting. The OR POST study guide has 8 sections and about 2,088 words.
01Operations Research Foundations and Model Formulation
This domain tests whether you can translate a messy decision into a defensible mathematical model and recognize its limits. Expect questions on variable definition, objective and constraint logic, deterministic versus stochastic models, model classes, validation, and sensitivity.
269 words, about 1 min02Linear Programming: Formulation, Geometry, and Duality
This domain tests formulation of linear programs, their geometric structure, and duality relationships. Expect extreme points, basic feasible solutions, binding constraints, shadow prices, reduced costs, complementary slackness, and infeasibility or unboundedness.
283 words, about 1 min03Network Optimization and Integer Programming
This domain tests network algorithms and integer modeling. Expect shortest path, minimum spanning tree, maximum flow/minimum cut, min-cost flow, assignment and transportation models, plus branch-and-bound, cutting planes, relaxations, and logical constraints.
258 words, about 1 min04Probability, Stochastic Processes, and Queueing Theory
This domain tests probability modeling and stochastic system performance. Expect conditional probability, Bayes rule, random variables, Poisson processes, Markov chains, Little's law, and queueing measures such as utilization, waiting time, and system length.
262 words, about 1 min05Decision Analysis, Utility, and Game Theory
This domain tests decisions under risk and strategic interaction. Expect decision trees, expected monetary value, expected value of perfect and sample information, risk attitudes, utility, dominant strategies, Nash equilibrium, mixed strategies, and zero-sum games.
267 words, about 1 min06Discrete-Event Simulation and Statistical Analysis
This domain tests simulation design and output analysis. Expect event scheduling, random-variate generation, input modeling, warm-up, replication, confidence intervals, common random numbers, verification, and validation.
258 words, about 1 min07Nonlinear and Dynamic Programming
This domain tests nonlinear optimization and sequential decision models. Expect convexity, Lagrange multipliers, KKT conditions, local versus global optima, Bellman's principle, stages, states, decisions, and recursive dynamic programming.
232 words, about 1 min08Applications, Modeling Practice, and Professional Ethics
This domain tests applied modeling judgment and professional conduct. Expect problem framing, stakeholder alignment, data provenance, model risk, documentation, sensitivity, communication of uncertainty, privacy, conflicts of interest, and honest reporting.
259 words, about 1 min