  Real-world decision and optimization problems, often involve constraints and
conflicting criteria. For example, choosing a travel method must balance speed,
cost, environmental footprint, and convenience. Similarly, designing an
industrial process must consider safety, environmental impact, and cost
efficiency. Ideal solutions where all objectives are optimally met are rare;
instead, we seek good compromises and aim to avoid lose-lose scenarios.
Multicriteria optimization offers computational techniques to compute Pareto
optimal solutions, aiding decision analysis and decision making. This reader
offers an introduction to this topic and has been developed on the basis of the
revised edition of the reader for the MSc computer science course
"Multicriteria Optimization and Decision Analysis" at the Leiden Institute of
Advanced Computer Science, Leiden University, The Netherlands. This course was
taught annually by the first author from 2007 to 2023 as a single semester
course with lectures and practicals. Our aim was to make the material
accessible to MSc students who do not study mathematics as their core
discipline by introducing basic numerical analysis concepts when necessary and
providing numerical examples for interesting cases. The introduction is
organized in a unique didactic manner developed by the authors, starting from
more simple concepts such as linear programming and single-point methods, and
advancing from these to more difficult concepts such as optimality conditions
for nonlinear optimization and set-oriented solution algorithms. Besides, we
focus on the mathematical modeling and foundations rather than on specific
algorithms, though not excluding the discussion of some representative examples
of solution algorithms.
