Introduction

A third important kind of data, other than images and text, are spreadsheets. We start off this module by creating a spreadsheet with code and then work with that data to approach a multi-objective problem — our case study is buying the best possible used car. We work with multiple attributes and want to take all of these into account. This leads us into the concept of Pareto dominance that allows us to discard options (cars) that are clearly inferior to others in all aspects (price, performance, etc.). We can then further ease decision making with filtering and visualization.

Learning outcomes

This module will help you do the following:

• Create and manipulate data frames
• Convert minimization problems into maximization problems and vice versa
• Compute Pareto dominance
• Apply restrictions to filter out undesirable solutions
• Visualize multi-dimensional data using coordinates, shapes, and colors

Warm-up

Warm-up assessment

The price-versus-quality scenario of the warm-up video is a very classical, straight-forward and obvious trade-off that pops up in numerous aspects of life. In your warm-up response, construct (with the powers of imagination) three more pairs (or combinations of more than two criteria) — each within the context of a specific applied scenario of your choosing — would lead to similar trade-off situations (meaning that options that are improvements in one sense are likely to worsen another criteria).

Concepts

After this module, you should be familiar with the following concepts:

• Data frame
• Multi-objective optimization
• Pareto dominance
• Pareto front

Remember that you can always look concepts up in the glossary. Should anything be missing or insufficient, please report it.