Applications of Linear Optimization
Building Linear Optimization Models
Building optimization models is more of an art
than a science.
Learning how to build models requires logical thought
facilitated by stu
Preprocessing the Data,
One way tabulation:
To determine the degree of item nonresponse
To locate blunders
To locate outliers (unusual observation)
To determine empirical distribution of the
Modeling Relationships and Trends in
Create charts to better understand data sets.
For cross-sectional data, use a scatter chart.
For time series data, use a line chart.
Common Mathematical Functions Use
Predictive Decision Modeling
Predictive modeling is the heart and soul of
Building decision models is more of an art than a
Creating good decision models requires:
- solid underst
Sampling is the foundation of statistical analysis.
Sampling plan - a description of the approach that is
used to obtain samples from a population prior to any
data collection activity.
A sampling pla
(Business) Analytics is the use of:
quantitative methods, and
mathematical or computer-based models
to help managers gain improved ins
Statistical inference focuses on drawing
conclusions about populations from samples.
Statistical inference includes estimation of population
parameters and hypothesis testing, which involves
Optimization is the process of selecting values of
decision variables that minimize or maximize
some quantity of interest.
Optimization models have wide applicability in
operations and supply chains, fin