Knowledge graph

Analytic hierarchy process

Linear programming model

• Leads to → Feasible region and graphical method
• Leads to → Simplex method

Mathematical modeling process

• Leads to → Assumptions and simplification

Overfitting and leakage

• Requires → Model validation and error measures

Regression modeling

• Leads to → Least squares and residual diagnostics

Sensitivity and robustness analysis

• Requires → Monte Carlo simulation
• Leads to → Model validation and error measures

Feasible region and graphical method

• Requires → Linear programming model

Least squares and residual diagnostics

• Requires → Regression modeling

Assumptions and simplification

• Requires → Mathematical modeling process
• Leads to → Copying templates without assumptions

Model validation and error measures

• Requires → Sensitivity and robustness analysis
• Leads to → Overfitting and leakage

TOPSIS ranking

Unit and scale inconsistency

• Requires → Dimensional analysis

Entropy weighting

Interpolation versus curve fitting

Simplex method

• Requires → Linear programming model
• Leads to → Duality and shadow price

Copying templates without assumptions

• Requires → Assumptions and simplification

Decision and state variables

• Leads to → Dimensional analysis

Dimensional analysis

• Requires → Decision and state variables
• Leads to → Unit and scale inconsistency

Duality and shadow price

• Requires → Simplex method

Fuzzy comprehensive evaluation

Standardization and scaling

• Leads to → Cluster analysis

Discretization

Integer programming

• Leads to → Branch and bound

Outlier handling

Branch and bound

• Requires → Integer programming

Principal component analysis

• Requires → Cluster analysis

Modeling report structure

Cluster analysis

• Requires → Standardization and scaling
• Leads to → Principal component analysis

Nonlinear programming and KKT conditions

• Leads to → Multi-objective optimization and Pareto front

Discriminant analysis

Multi-objective optimization and Pareto front

• Requires → Nonlinear programming and KKT conditions

Shortest path models

Time series and exponential smoothing

• Leads to → ARIMA and differencing

ARIMA and differencing

• Requires → Time series and exponential smoothing

Network flow models

Monte Carlo simulation

• Leads to → Sensitivity and robustness analysis

Minimum spanning tree

Transportation and assignment problems

Knapsack problem

Traveling salesman routing

Dynamic programming recursions

Queueing and inventory models

Population and growth models

Compartmental differential equation models

Difference equation models

Markov chain prediction