Postgraduate Course: Combinatorial Optimization (MATH11030)

Course Outline
School	School of Mathematics	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 11 (Postgraduate)	Availability	Not available to visiting students
SCQF Credits	5	ECTS Credits	2.5
Summary	This module will address both optimal and heuristic approaches - cutting plane, branch-and-bound, branch-and-cut, Lagrangian relaxation, local search, simulated annealing, tabu search, genetic algorithms, and neural networks - to solving combinatorial optimization problems such as production planning and scheduling, operational management of distribution systems, timetabling, location and layout of facilities, routing and scheduling of vehicles and crews, etc.
Course description	Not entered

Entry Requirements (not applicable to Visiting Students)
Pre-requisites		Co-requisites
Prohibited Combinations		Other requirements	None

Course Delivery Information
Not being delivered

Learning Outcomes
Ability to formulate a wide range of management problems that can be solved to optimality by classical combinatorial optimization techniques and the knowledge of alternative solution approaches such as metaheuristics that can find nearly optimal solutions. Awareness how difficult some practical optimization problems can be and the complex role performed by managers.