ABSTRACT
When making choices one is faced with different perspectives wishing to make the best decision with respect to each one of them. However, this is not always possible. In fact, rarely those perspectives lead to the same “best” option since there is not a single decision that performs best on all perspectives. In the previous book chapters, several methods have been presented addressing problems where the Decision Marker has a finite number of alternatives and aims at selecting the best one considering several points of view. Multi-Objective Linear Programming is, within Mathematical Programming, the area that tackles linear optimization models with multiple objectives. The importance of this optimization approach is shown by the large spectrum of applications one can find in the literature. In this chapter main concepts in Multi-Objective Linear Programming are addressed, setting the basis to fully understand the chapters that follow within this book. Concepts as “efficient and non-dominated solutions”, “solution and objective function spaces”, “weakly efficiency”, among others, will be presented. Some of their limitations will be discussed. Examples will illustrate all concepts throughout the chapter. At the end, some final remarks are made concerning the articulation of Decision Maker’s preference information. A set of exercises covering all topics is proposed at the end of the chapter.
