Regression-based approaches to identify relationships between predictor variables and future values in forecasting. The problem is formulated with decision variables representing production quantities, workforce levels, and inventory across periods. The objective minimizes total costs including production, inventory holding, and shortage costs subject to demand, capacity, and inventory balance constraints. Table of Contents: - Aggregate planning problem definition and planning horizon - Demand aggregation across products and time periods - Decision variables: production rate, workforce, inventory, backorders - Constraint formulation: demand satisfaction, capacity, inventory balance - Cost components: production, inventory holding, workforce hiring/firing, backordering - Objective function: total cost minimization - Linear programming formulation structure and standard form - Feasible region and optimal solution properties - Simplex method and tableau representation - Basic and non-basic variables in tableau format - Optimality conditions and stopping criteria - Sensitivity analysis and shadow prices (dual values)
Regression-based approaches to identify relationships between predictor variables and future values in forecasting. The problem is formulated with decision variables representing production quantitie…