DESCRIPTION
Multiple criteria decision making (MCDM) is a subfield of operational research that deals with the methods and tools to facilitate decision-making process in problems involving multiple conflicting criteria. It has applications in diverse domains such as business, supply chain, energy, healthcare, sustainability and logistics. This course will cover the theory of MCDM and various approaches to deal with decision problems with multiple criteria and tackle multi-objective optimisation problems.
Main contributors: Dr Banu Lokman (Course Leader), Professor Dylan Jones
PRE-REQUISITES
The basics of mathematical programming
AIMS OF THE COURSE
The course aims to develop knowledge of the theory of MCDM and develop skills in building and solving optimisation problems with multiple objectives.
LEARNING OUTCOMES
On completion of the course, students will be expected to:
• Understand the properties of efficient solution alternatives in decision problems with multiple objectives
• Build and solve mathematical models to find nondominated solutions of multi-objective optimisation problems
• Understand and apply the goal programming method to solve decision problems with multiple goals
PRINCIPAL TOPICS OF STUDY
• Introduction to multi-criteria decision making and classification.
• Efficiency and Nondominance
• Scalarization Techniques in Multi-objective Optimisation
• Exact & Approximate Solution Methods
• Goal Programming
ASSESSMENTS
Assessment, a summative assessment exercise, will be held in the third day. It will typically last about half-an-hour. Feedback will be provided before the end of the course.
OUTLINE
Day 1
12.30 – 13.30 Registration and lunch
13.30 – 14.40 Introduction to multi-criteria decision making.
14.40 – 15.00 Tea/Coffee Break
15.00 – 17.00 Efficiency and Nondominance. Definitions of Optimality.
Day 2
9.00 – 10.40 Scalarization Techniques in Multi-objective Optimisation – Part 1
10.40 – 11.00 Tea/Coffee Break
11.00 – 12.30 Scalarization Techniques in Multi-objective Optimisation – Part 2
12.30 – 13.30 Lunch
13.30 – 14.40 Exact & Approximate Solution Methods
14.40 – 15.00 Tea/Coffee Break
15.00 – 17.00 Case Study 1: A Real-life Sales Territory Construction Problem
Day 3
9.00 – 10.40 Goal Programming: Theory and Applications – Part 1
10.40 – 11.00 Tea/Coffee Break
11.00 – 12.30 Goal Programming: Theory and Applications – Part 2
12.30 – 13.30 Lunch
13.30 – 14.40 Discrete Choice Theory and Applications
14.40 – 15.00 Tea/Coffee Break
15.00 – 15.30 Assessment
15.30 – 16.40 Case Study 2: Goal programming and the Analytical Hierarchy Process (AHP) in the offshore wind sector
16.40 – 17.00 Concluding Remarks & Feedback Session