2. Quantitative Analysis & its Steps

Quantitative Analysis

Procedures for finding the “best” or optimal solution through model development and solving.

Model Development

The process of creating representations of real objects or situations in various forms.

Iconic Models

Physical replicas of real objects, such as car or plane models.

Analog Models

Physical models that do not resemble the object they represent, like gas meters or thermometers.

Mathematical Models

Represent real-world problems using mathematical formulas based on assumptions and statistical analyses.

Objective Function

A mathematical expression that defines the goal of the model, such as maximizing profit or minimizing cost.

Constraints

Restrictions or limitations that must be adhered to in the model, such as production capacities.

Uncontrollable Inputs

Environmental factors outside the decision-maker's control, like profit per unit or production time.

Controlled Inputs

Factors specified by the decision-maker, such as the number of product units to produce.

Deterministic Model

A model where all uncontrollable inputs are known and fixed.

Stochastic Model

A model where uncontrollable inputs are uncertain and can vary, making it more complex to analyze.

Cost/Benefit Considerations

Evaluations made when selecting a mathematical model, balancing complexity and cost.

Data Preparation

The process of organizing and ensuring the accuracy of data before model implementation.

Model Solution

The process of identifying the alternative that provides the optimal output for the model.

Feasibility

A condition where an alternative satisfies all model constraints, making it a candidate for the best solution.

Model Testing and Validation

The process of assessing the accuracy of a model by generating solutions and comparing them to expected outcomes.

Report Generation

The creation of a managerial report summarizing the model results and recommendations for decision-makers.