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Operations Research and Optimization
1. Introduction to Operations Research
2. Mathematical Foundations for Optimization
3. Linear Programming
4. Network Optimization
5. Integer Programming
6. Nonlinear Programming
7. Dynamic Programming
8. Stochastic Processes and Queuing Theory
9. Simulation Modeling
10. Decision Analysis
11. Heuristics and Metaheuristics
12. Advanced Optimization Topics
Decision Analysis
Decision Problem Structure
Decision Elements
Decision Maker
Decision Alternatives
States of Nature
Outcomes
Decision Environment
Certainty
Risk
Uncertainty
Payoff Tables
Payoff Matrix Construction
Profit Payoffs
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Regret Tables
Decision Making Under Uncertainty
Decision Criteria
Maximax Criterion
Maximin Criterion
Minimax Regret Criterion
Laplace Criterion
Hurwicz Criterion
Criterion Selection
Risk Attitude
Problem Context
Criterion Comparison
Decision Making Under Risk
Expected Value Approach
Expected Monetary Value
Expected Opportunity Loss
Risk-Neutral Decision Making
Decision Trees
Tree Construction
Chance Nodes
Decision Nodes
Rollback Analysis
Sensitivity Analysis
Value of Information
Expected Value of Perfect Information
Expected Value of Sample Information
Information Economics
Utility Theory
Utility Functions
Utility Axioms
Utility Assessment
Utility Curves
Risk Attitudes
Risk Aversion
Risk Neutrality
Risk Seeking
Expected Utility Maximization
Utility-Based Decisions
Certainty Equivalent
Risk Premium
Multi-Attribute Utility
Multiple Objectives
Attribute Scaling
Utility Independence
Behavioral Decision Making
Cognitive Biases
Anchoring Bias
Availability Heuristic
Representativeness Heuristic
Prospect Theory
Reference Points
Loss Aversion
Probability Weighting
Group Decision Making
Group Dynamics
Consensus Building
Voting Methods
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11. Heuristics and Metaheuristics