Course Details in

Module Title	LM Heuristic Optimisation
School	Mathematics
Department	Mathematics
Module Code	06 19611
Module Lead	Sandor Nemeth
Level	Masters Level
Credits	10
Semester	Semester 2
Pre-requisites
Co-requisites
Restrictions	Optional for all MSci programmes in Mathematics and all MSci JH programmes including Mathematics
Contact Hours	Lecture-23 hours Tutorial-5 hours Total: 28 hours
Exclusions
Description	Most problems from management mathematics (discrete or continuous) are NP-hard. In other words, optimisation problems that arise in industry or in the public sector could not be solved exactly in reasonable computing time, even with modern computers. Therefore, when traditional mathematics techniques fail to give a fast answer, one should rely on near-optimal solution methods or heuristics. Ideas of classical heuristics (local search, hill climbing, greedy search, divide and conquer, A* search, dynamic programming etc.) will be studied first. A modern heuristics (metaheuristics) or general frameworks for building heuristics, usually gives rules of escaping from the so-called "local optima trap". Such methods are Tabu search, Simulated Annealing, Evolutionary Algorithms, Genetic Algorithms etc.
Learning Outcomes	By the end of the module the student should be able to: Understand and explain why and when heuristic optimisation techniques are useful in Management Mathematics Understand and explain the basic concepts of classical heuristic optimisation techniques Design data structure for the computer code and apply rules of heuristics for that problem Explore this topic beyond the taught syllabus
Assessment	19611-01 : Raw Module Mark : Coursework (100%)
Assessment Methods & Exceptions	90% based on a 1.5 hour written examination in the Summer Term; 10% based on work during term-time.
Other	None
Reading List	Other literature, recommended at the end of lectures; S. Russel, P. Norvig: Artificial Intelligence: A modern approach, Prentice Hall, Second Edition, 2002, ISBN 0137903952; Z. Michalewicz, D.B. Fogel: How to solve it: Modern heuristics, Springer, Corrected Third Printing 2002, ISBN 3-540-66061-5;