RETURN TO DECISION ANALYSIS SYLLABIQuantitative Methods for Problem Solving
Provider - School of Systems Engineering, Policy Analysis, and Management, Delft
University of Technology
- Department of Policy Analysis
- Instructor: Dr. G.E.G. Beroggi
Place of course in curriculum
- Study phase: third year
- Form: lectures, case studies, computer labs
- Status: mandatory
- Total hours: 80
Prerequisites
Introduction to Policy Engineering Management, Advanced Policy Engineering
Management, Linear Algebra, Discrete Mathematics.
Goal
The goal is to introduce the students to the art and science of decision
modeling in policy management and to learn the applications and the
potential of quantitative decision modeling for complex problem solving.
After having taken the course the students must be able to understand and
develop basic decision models, interpret the results and communicate them
to
non-analytical decision makers.
Content (chapters refer to the text book):
week 1 Chapter I: The problem solving process in policy planning;
criteria,
goals, alternatives, uncertainty, and decision makers; relations and
preferences; descriptive and normative decision making.
week 2 Chapter II: The analytic modeling process; structural,
formal, and
resolution model; the elements of decision modeling; interactive consistent
strong preference assessment.
week 3 Experiment 1: Part 1: Structural modeling with VIDEMO
(software package);
Part 2: Preference ordering with strong preference method, sorting algorithm,
and direct assessment.
week 4 Chapter III: Criteria weighting, decomposition, and reduction;
resolution of inconsistencies in preference assessment; visualization of
multicriteria assessments.
week 5 Chapter IV: Descriptive choice models; evaluation of dominance,
inferiority, and incomparability of alternatives; sensitivity in preference
assessment.
week 6 Experiment 2: Criteria definition and alternative evaluation
with
hierarchical decomposition approach; criteria reduction.
week 7 Case study 1: The Falkland Islands conflict; nuclear waste
management; specialization of hospital services; subway line extension
in
Paris.
week 8 Chapter V: Normative decision models with deterministic
outcomes;
preferential independence; additive preference models; preference
elicitation; scaling of conditional preferences; evaluation of alternatives
and sensitivity analysis.
week 9 Chapter VII: Normative decision models with uncertain
outcomes;
preferential and utility independence; additive and multiplicative
preference models; utility elicitation; scaling of criteria; evaluation
of
alternatives and sensitivity analysis.
week 10 Case Studies 2: Selection of nuclear repository site;
comparison of
hazardous materials transportation modes; European Community decision
making; airport development.
week 11 Experiment 3: (Chapter IX) Multiactor decision making;
social
choices; aggregation of preferences; voting procedures; group decision
making and conflict resolution.
week 12 Chapter X: Mixed-valued alternatives; multigoal problems;
graphical
representation of two-criteria problem; analytical resolution of problem;
computer use for problem solving; sensitivity analysis.
week 13&14 Case Study 3: Transportation planning, routing,
nurse scheduling,
two-actor zero-sum conflict situations, mixing chemical substances.
Work approach
The class will be given as lectures, accompanied case studies, and computer
labs. The weeks 3, 6 and 11 are reserved for experiments; weeks 7, 10,
13
and 14 are reserved for case studies. The three experiments and the three
case studies are mandatory. Knowledge of EXCEL is expected, the software
package VIDEMO will be introduced.
Exams
The final grade is determined by a written examination over all material
treated in the textbook, the content of the experiments, and the case
studies. Only students who participated in the mandatory tasks can
participate in the experiment.
Study material
Text book "Decision modeling in policy management" and selected
articles
which will be handed out in class.