Project Title: A Tutorial for Heuristic Local Search
Student: Maria Zapiti
Course: MSc Management of IT
	
Abstract:
Heuristic local search is a basic technique used in many 
heuristic and metaheuristic algorithms. Heuristic and 
metaheuristic algorithms have been an area of intensive 
research in the field of optimisation and search algorithms. 
The reason for their popularity is because they can be 
used for solving large-scale real-world problems efficiently. 
The purpose of this dissertation is to create a computer-based 
tutorial system that could present the basic concepts around 
heuristic techniques effectively, emphasising basic local 
search strategies. The general aim is to provide, to novices 
in the area, the necessary knowledge in order to be able to 
proceed in further studies. For the creation of such an 
environment, research has been done in the field of heuristic 
local search techniques. Important concepts and ideas were 
collected and organised in such a way that can facilitate 
the teaching of heuristic local search from its principle 
and motivation to the specific design and implementation 
issues. In order to present the concepts in a readable and 
effective way, basic guidelines concerning the screen layout, 
text presentation, users? navigation and user assessments 
were followed. Users? assessments, in the form of interactive 
tasks, were found to be the most effective in engaging and 
increasing the interest and understanding of the learners 
throughout the learning process. Moreover, a problem-based 
approach was used for introducing new concepts and ideas 
while using a realistic example. For this purpose, the 0-1 
Knapsack problem was used as a means to provide discussion 
points and general consideration while implementing a local 
search algorithm that could be used for solving such a problem. 
By the end of the tutorial, users are able to test with their 
own data a small instance of the Knapsack problem and compare 
the performances of some different local search strategies 
that were presented previously.