At the end of this course, the students; 1) Gain an ability to design and conduct experiments, as well as to analyze and interpret data 2) Gain an ability to identify, formulate, and solve engineering problems 3) Gain an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
The description and structure of production systems, heuristic search methods in production planning, branch-and-bound technique, local search, tabu search, simulated annealing, genetic algorithms, heuristic scheduling methods, neighborhood search, makespan minimizing techniques, weighted tardiness problems, bottleneck heuristics.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Concepts of optimization, local optimum, global optimum
2nd Week
NP-hard problems and their complexity
3rd Week
Basic heuristic methods: random search, Hill Climbing algorithms
4th Week
The application of these algorithms on an example problem
5th Week
The General review of modern heuristic algorithms and applications
6th Week
Basic principles of evolutionary algorithms and application areas
7th Week
The application of evolutionary algorithms on an example problem
8th Week
Midterm
9th Week
Basic principles of genetic algorithms and application areas
10th Week
Basic principles of simulated annealing and application areas
11th Week
The application of simulated annealing algorithms on an example problem
12th Week
Basic principles of Tabu Search algorithms and application areas
13th Week
The application of Tabu Search algorithms on an example problem
14th Week
Project presentation
RECOMENDED OR REQUIRED READING
Modern Heuristic Techniques for Combinatorial Problems Colin Reeves, John Wiley,1993
