Schedule

Period	:	week 37 (2014)–week 51 (2014), week 2 (2015)–week 4 (2015).
When	:	every Monday from 09:00–12:45
Where	:	room 514 of the FG (Freudenthal Gebouw).

Report deadlines

The procedure of handing in either of your reports is required to meet the following criteria:

1. The report should be handed in on paper during class or in the teacher's postbox. In the later case, send an e-mail to notify the teacher.
2. All associated source code and a PDF file of your report need to be sent to teacher's email address.

For each workday your report is late (past the deadline, rounded up) a full point will be taken from your grade to a minimum of 0 points. The recommended size for your report is around 20 pages. Both reports should be written in English and created with LaTeX.

Nov 17 (9:00 AM)	:	Topic 1, random number generation and Monte Carlo integration. Hand in on paper at the teacher (or teacher's postbox).
Jan 23 (5:00 PM)	:	Topic 2, optimisation with genetic algorithms. Hand in on paper at the teacher (or teacher's postbox).

Weekly Schedule

Note: The “weekly schedule” below for the weeks to come have been copied from last years course (note that the references to the Lecture Notes have been adapted to the 2014 edition) and are subject to changes (updates).

Weekno.	Treated subjects	Material
	As an introduction to generating random numbers it might be fun/instructive to watch the YouTube movie “Random Numbers-Numberphile” (11.32 min).
37 (Sep 8) FG514	Introduction to course setup, assignments, report deadlines and grading. Introduction to random number generator (RNG) theory. In lab: Assignment 'Getting Started'. In lab: If done, start implementing the RNGs (Exercise 2.6). See Table 2.1 for example RNG parameters. When your code seems to work, also do Exercise 2.2. Finally, add some reasonable RNGs on your own as well. At home: read lecture notes up to Sec. 2.3	rngmc.tar.gz generators API ref C++ tutorial
38 (Sep 15) Min205	Schrage's trick, implementation issues (Sec. 2.3). RNG testing (Sec. 2.5, Exercise 2.12). In lab: Program RNGs (see last week), test uniformity and correlation in MATLAB (using plotrand, plotpoints, and write your own random walk plotter in MATLAB). Graded assignment: 'Bit Randomness' in two weeks. Optional: diehard testing, chi-squared testing.	Recommended material: Park & Miller.
39 (Sep 22) Min016	Generating numbers with a non-uniform distribution (Sec. 2.4). In lab: Implement the rejection method, Exercise. 2.9 in the course book, using nonuniform.cc. Graded assignment: hand in (pen and paper is fine) answers to Exercises 2.7 and 2.8 from the lecture notes in two weeks.
40 (Sep 29) Min022	Hand in 'Bit randomness' assignment. Trapezoidal rule and the curse of dimensionality (Sec. 3.1). Introduction to Monte-Carlo integration, and multidimensional Monte-Carlo (Sec. 3.2). In lab: finish RNGs and testing in MATLAB. In lab: If done, 1D Monte-Carlo and integration of the d-dimensional unit sphere (Exercise 3.4 & 3.8). Follow these guidelines. Note: this is the last RNG week, make sure to have sufficiently tested the generators of Table 2.1, and some generator(s) of your own.
41 (Oct 6) BBG017	Hand in exercises 2.7 and 2.8 from the lecture notes. In lab: work on Chapter 3 (most notably the Monte Carlo methods and unit sphere integration).
42 (Oct 13) BBG017,Min207	In lab: work on part I code and report. Note: next week we start with the second part of the course, Genetic Algorithms (GAs). The deadline for the first report is the 17th of November (2014), before 9:00 AM.
43 (Oct 20) BBG017	Start Topic 2, Genetic Algorithms. Intro optimisation problems. Bit representation and modification. GA theory: objective functions, fitness functions, mutation, roulette wheel selection, crossover, stopping criteria (Sec 4.1). At home: read Section 4.2. In lab: Startup exercises Genetic Algorithms. In lab: start implementing objective functions, fitness functions, mutation, roulette wheel selection, crossover and stopping criteria. Graded assignment: Applying Genetic Algorithms. Hand in two sessions from now; 10th of November.	galib.tar.gz GALib API ref ga_assign.pdf
44 (Oct 27) BBG017	Elitism, Gray codes (Sec. 4.3), and local optimisation. In lab: work on base GA code (See week 43). In lab: if done, start on Function minimisation exercise. In lab: if done, start implementing elitism, Gray codes.
45 (Nov 3)	Exams in the bachelor program. No classes.
46 (Nov 10)	Hand in Applying Genetic Algorithms assignment. In lab: work on GA code and function minimisation.
47 (Nov 17)	9:00 AM Deadline for report I. Hand in on paper at the teacher (teacher's postbox). Send in your code and PDF by e-mail. Look at report requirements here and at the main page.
47 (Nov 17)	In lab: finish the Function minimisation exercise. In lab: finish elitism, Gray codes. In lab: test effectiveness of elitism and Gray codes on the FunMin problem.
48 (Nov 24)	Charges on a sphere (Sec. 4.4.3). Charges on a Sphere demo. In lab / at home: finish elitism, Gray codes, and testing these on the FunMin problem. Make sure all your GA code functions properly. When you have finished FunMin and all galib parts, get started on the final problem assignment. Graded assignment: exercise 4.10. Hand in two weeks from now; 8th of December.
49 (Dec 1)	Travelling salesman problem (Sec. 4.4.1). Travelling Salesman Problem demo. Site to find more TSP problems and, sometimes, their proven optimal solutions: TSPlib. In lab / at home: think about your final optimisation topic; choose either charges on a sphere, TSP, or KP. Note you can use suspend/resume functionality to do multi-stage genetic optimisation.	TSP demo SPH demo galib_problems.tar.gz
50 (Dec 8)	Hand in exercise 4.10 from the lecture notes. Local search. In lab / at home: choose and work on your final assignment.
51 (Dec 15)	In lab / at home: work on your final assignment.
52 – 1	Holidays. No classes.
2 (Jan 6)	In lab / at home: work on your final assignment.
3 – 4	If not done, complete the code for your final problem and run experiments. Complete all starred exercised from Chapter 4, and check the requirements for spherecharges (here) and TSP (here). Run experiments to obtain as good solutions as possible to either the TSP, the spherecharges problems, or KP. Note: no classes during this period.
4 Jan 23	5:00 PM Deadline for report II. Hand in on paper at the teacher (or teacher's postbox). Send in your code and PDF by e-mail. Look at report requirements here and at the main page.