Decision Support Models


By the end of this course, students will have acquired knowledge, skills, and abilities that will enable them to

- Know and understand basic concepts of decision theory

- Understand issues related to the subjectivity inherent in decision making and how different methodologies model this subjectivity

- Identify multiobjective linear programming (PLMO) problems

- Apply various methods to obtain compromise solutions to PLMO problems

- Model and solve problems that may arise in real-world situations.

General characterization





Responsible teacher

Maria Isabel Azevedo Rodrigues Gomes


Weekly - 4

Total - 56

Teaching language



Available soon


Anderson et al – Quantitative Methods for Business (2001) – SW College Publicating

Antunes, C. H., Alves, M. J., & Clímaco, J. (2016). Multiobjective linear and integer programming. Cham: Springer.

Gomes, M.I. e Chibeles-Martins N. (2023). Mathematical Models for Decision Making with Multiple Perspectives An Introduction, CRC Press.

Goodwin, P. e Wright, G. – Decision Analysis for Management Judgement (2014 - 5th ed.) – John Wiley & Sons

Hillier, Lieberman, Introduction to Operations Research, Mc Graw - Hill, 10th ed (2015) - or any other edition

Saaty, T. L.– The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation (1990) – RSW Publications

Steuer, R. E.– Multiple Criteria Optimizations: Theory, Computation, and Application (1986) – John Wiley & Sons

Teaching method

Classroom classes

Evaluation method

1 -  Attendance

All students must achieve FREQUENCY in order to have access to the 2nd  test and/or the exam. This “frequency” can be obtained by attending at least two-thirds of the classes taught during the semester. The “frequency” obtained during a school year remains valid for the following school year in case of failure.

2 - Evaluation

Any student enrolled in the course may take the exam, provided they have attended the class or are exempt from taking the exam. Class approval can be obtained in one of two ways: Continuous assessment or Exam.

2.1 - Continuous assessment

Continuous assessment consists of 3 elements: 2 tests, with a maximum duration of 90 minutes each, and a group assignment.

All students are admitted to the 1st  test. Students will be admitted to the 2nd test if they have obtained “frequency”.

Each test is scored out of 7 (seven) to 9 (nine) points and the group assignment is scored out of 4 (four) points. A student passes if the sum of all scores, rounded to the nearest whole number, is greater or equal to 10 points.

2.2 – Assessment by Exam

All students who have "Frequency" will be admitted to the written exam. The maximum time allowed for the exam is 3 hours. A student passes the exam if they score a minimum of 10 points on the exam.

FINAL NOTE: "Grade Improvement" requires proper enrollment in the Academic Division as outlined in FCT NOVA''s current grading policy.

Subject matter

1 – Single criterion decision: Decision and Uncertainty; Decision and Risk; Sequential Decisions and Decision Trees; Utility Theory;

2 – Multi Criteria Decision: Compensatory Models – SMART Technique Non-Compensatory Model – ELECTRE Methodology; Hierarchic Models – AHP.

3 – Multi Objective Optimization: Solutions and Objectives. Dominance and Efficiency; Aggregated Sums Models; Weight Vectors Models; Change of Scale; Reduction of Feasible Region; Goal Programming; Interactive Models: STEM.


Programs where the course is taught: