Explore UCD

UCD Home >

MIS41480

Academic Year 2025/2026

Problem Solve with Heuristics (MIS41480)

Subject:
Management Information Systems
College:
Business
School:
Business
Level:
4 (Masters)
Credits:
7.5
Module Coordinator:
Dr Istenc Tarhan
Trimester:
Summer
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Optimization problems are everywhere in daily life, from managing a monthly budget to allocating available time across multiple subjects. In this module, we explore structured, scientifically grounded approaches to these intuitive decision-making processes, known as heuristics.

Heuristic algorithms provide practical solutions to complex problems, often guided by experience or intuition. This module explores shared structures in optimization problems, contrasts heuristic and non-heuristic approaches, and examines when heuristics are most effective.

We will study the fundamentals of heuristic algorithms and identify the common attributes of efficient heuristic algorithms. Metaheuristics, that are high-level frameworks designed to guide the development of heuristic algorithms, will be studied as a way to leverage these common attributes. Next, heuristic algorithms with different scopes will be discussed, such as multi-objective heuristics and matheuristics.

A case study will be conducted to investigate the use of AI tools in the development of heuristics. Students will have the opportunity to develop their own solution algorithm for a real-life logistics problem observed in different contexts, such as supermarket food redistribution and e-commerce fashion.

About this Module

Learning Outcomes:

1. Identifying different optimization problems and disclosing their common ground
2. Recognizing the trade-offs between exact and heuristic approaches, and their distinct advantages and disadvantages
3. Distinguishing common attributes of efficient heuristic algorithms
4. Analysing several well-known metaheuristic algorithms
5. Modelling heuristic algorithms in a generic framework and design fair experimental procedures to evaluate their performance
6. Developing and applying a new heuristic algorithm to solve a real-world problem

Indicative Module Content:

1 18.05.2026 Introduction: Classic optimization problems, their classification, example applications
2 19.05.2026 Exact vs heuristic algorithms: Trade-offs
3 25.05.2026 History of heuristics
4 26.05.2026 Fundamental concepts in heuristics
5 02.06.2026 Single solution-based metaheuristics 1
6 15.06.2026 Single solution-based metaheuristics 2
7 16.06.2026 Computational experiments with heuristics
8 22.06.2026 Population-based metaheuristics
9 23.06.2026 Other types of heuristic algorithms
10 30.06.2026 Using AI to develop heuristics

Student Effort Hours:
Student Effort Type Hours
Lectures

28
Specified Learning Activities

40
Autonomous Student Learning

100
Total

168

Approaches to Teaching and Learning:
A predominantly face to face teaching approach will be used with face-to-face lectures.

Activities include:

- Problem-based learning
- Group work
- Face-to-face lectures

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): A final exam (pen and paper in person) that will cover all subjects studied throughout the term End of trimester
Duration:
2 hr(s)
 Standard conversion grade scale 40% No
50
 No
Group Work Assignment: Development of heuristic algorithms for real-life problems Week 14 Standard conversion grade scale 40% No
50
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Summer Lecture Offering 51 Week(s) - 37, 38, 41, 42 Mon 10:00 - 12:50
Summer Lecture Offering 51 Week(s) - 37, 38, 39, 41, 42 Tues 14:00 - 16:50
Summer Lecture Offering 51 Week(s) - 43 Tues 14:00 - 16:50
Print this page
Fill in the following details:
Enter the body of your query here.

From time to time UCD would like to send you further information that we feel, based on your enquiry, would be of interest to you.