Decision Making Systems & Decision Theory - 2023 entry

In today’s business environment, procedural decision-making is a routine daily activity for managers. Decisions must be made in dynamic and complex environments and factor in many risks and uncertainties. It is therefore crucial for managers and policy makers to understand the nature of decision-making processes and to develop strategies for choosing best alternatives among all possible options. In this module, you will learn about the theories and motivations behind decision-making processes, individual and group decision-making, and descriptive and prescriptive approaches. Moreover, decision analysis will be conducted via modelling the uncertainty and risks on daily examples and solution approaches using machine learning techniques such as Bayesian Statistics, Decision Trees, Game Theory, Monte Carlo simulation. Further, theories and techniques for multi-criteria decision-making processes will be demonstrated. Finally, you will explore applied decision support systems through case study analyses.

This module aims to provide the theories and motivations behind decision-making process, individual and group decisions. The intended learning outcome from this module is to demonstrate rational decision-making models and techniques, and related factors such under uncertain and risk conditions. This module examines the principles and algorithms for making decisions. It provides a more precise and systematic study of the formal or abstract properties of decision-making scenarios. The module considers decisions of a single individual and situations where the decisions of more than two parties are involved. Topics covered in the first part include: subjective probability, rational preferences and utility, expected utility, risk aversion, objections and alternatives to expected utility theory, and group decisions. In addition, the module will also cover several decision-making algorithms for complex and multi criteria multi decision making problems.

On successful completion of this module you should be able to:

ILO #1 understanding decision process and decision theory E1

 ILO #2 comprehend the probability concept, Bayes theorem, Game theory and the decision modelling under certain, uncertain and risk involved conditions E1

ILO #3 understand the Utility theory and decision functions (loss function, minimax and more), Pareto optimality and related concepts E1

 ILO #4 grasp the Multiple-Criteria Decision Making E1

 ILO #5 understand Decision Trees E1

 ILO #6  understand Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), TOPSIS ELECTRE methods E1

ILO #7 grasp other decision-making approaches E1

ILO #8 apply popular and modern decision-making technologies in industrial and commercial environment E1

ILO #9 demonstrate modelling capability of the advanced decision theory in complex industrial and engineering problems E1

ILO #10 analyse the decision-making requirements in industrial and engineering problems E1

ILO #11 apply enhanced problem-solving ability in the fields of decision theory and multi criteria decision making problems E1

ILO #12 develop communication skills E1

ILO #13  demonstrate report writing skills, project management and organisational skills E1

 AHEP ILOs - BEng 

 All attribute values mapped against this module: SM1p, EA1p, EA3p, D1p, D3p, EP1p, D4p, EP4p, ET6p, G1p, G2p, G3p, G4p,

AHEP ILOs - MEng 

All attribute values mapped against this module: SM1m, EA1m, EA3m, D1m, D3m, EP1m, SM5m, D4m, EP4m, ET6m, G1m, G2m, G3m, G4m.

1: Introduction to decision theory and decision matrix and decision-making process:

2: Decision modelling, utility theory, under deterministic, uncertain and risk circumstance:

 3: Pareto optimality:

4: Probability concept, Bayes theorem, Game theory: 

 5: Multi-criteria multi decision making:

 6: Decision trees:

 7: AHP and ANP method: 

 8: TOPSIS method:

9: ELECTRE method:

Reassessment will be by written exam. For deferred candidates, the module mark will be uncapped. For referred candidates, the module mark will be capped at 40%.

Basic reading:

ELE:

Web based and Electronic Resources:

Other Resources:

Reading list for this module: