CHAIR OF

COMPUTATIONAL

INTELLIGENCE

--- Exam Review EMO from 23rd to 26th August ---

Due to maintenance work on the E-learning System, the review time for the EMO exam will be extended until Thursday, 26th August 2021, 23:59 (Middle European Summer Time - UTC+2). In addition, there will be another Zoom Meeting for asking questions on Thursday, 26th August from 13:00 to 14:00 o'clock.

All participants of the exam have received an email with further details and the zoom-call information.

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--- Exam EMO on July 12th ---

The exam will be done in an unsupervised online format on 12th July, using the E-learning (Moodle) system. If you have registered for the exam, you should have gotten various emails already, regarding the rules and organization of the exam, and you should have access to the exam-course in the system (Link).

If, by any chance, you have registered for the exam but can not access this course or you did not receive any emails from us yet regarding the exam rules, please contact us as soon as possible.

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Concept of the online course: 

• The recorded lectures are provided to you via mediasite.
• The exercises are performed as live sessions via ZOOM.
• There is a forum on the e-learning plattform of OVGU (moodle).
• Registration for the exercises via LSF.
• This webpage will be updated during the course, please regularly check for updates.

Description

In our daily lives we are inevitably involved in optimization. How to get to the university in the least time is a simple optimization problem that we encounter every morning. Just looking around ourselves we can see many examples of optimization problems even with conflicting objectives and higher complexities. It is natural to want everything to be as good as possible, in other words optimal. The difficulty arises when there are conflicts between different goals and objectives. Indeed, there are many real-world optimization problems with multiple conflicting objectives in science and industry, which are of great complexity. We call them Multi-objective Optimization Problems.
Over the past decade, lots of new ideas have been investigated and studied to solve such optimization problems as any new development in optimization which can lead to a better solution of a particular problem is of considerable value to science and industry. Among these methods, evolutionary algorithms are shown to be quite successful and have been applied to many applications.

This course addresses the basic and advanced topics in the area of evolutionary multi-objective optimization and contains the following content:

• Introduction to single-objective optimization (SO) and multiobjective optimization (MO), classical methods for solving MO, definitions of Pareto-optimality and other theoretical foundations for MO
• Basics of evolutionary algorithms (algorithms, operators, selection mechanisms, coding and representations)
• Evolutionary multi-objective algorithms (NSGA-II, EMO scalarization methods such as MOEA/D)
• Constraint handling in SO and MO, robust optimization in EMO, surrogate methods for expensive function evaluations
• Evaluation mechanisms (Design of experiments, test problems, metrics, visualization)

Team

• Sanaz Mostaghim (Lectures)
• Heiner Zille (Tutorials) (Email: heiner.zille@ovgu.de)
• Maik Büttner (Tutorials) (Email: maik.buettner@st.ovgu.de)
• Welf Knors (Tutorials) (Email: welf.knors@st.ovgu.de)
• Hans-Martin Wulfmeyer (Tutorials) (Email: hans-martin.wulfmeyer@st.ovgu.de)

Lectures 

The lectures will start in an online format (due to the current situation). We will provide you the recorded lectures which you can access from home at anytime.

Lecture Plan

In order to plan the lectures in a structured way, we provide you the following lecture plan. You should learn the material for the corresponding specified week by referring to the online videos and slides:

Slides

To open the slides, you need to use a password which is specified in the recorded lecture "Organization for SS2020" (access information above).

Password for the slides are announced in the tutorials and in the E-learning (Moodle) course.

• Chapter 0: Organization 
• Chapter 1: Introduction 
• Chapter 2: Basic Principles of Multi-Objective Optimization 
• Chapter 3: Evolutionary Algorithms (Updated 31.05.2021)
• Chapter 4: Multi-Objective Evolutionary Algorithms (Updated 31.05.2021)
• Chapter 5: Robust Optimization and Constraint Handling
• Chapter 6: Evaluation mechanisms

Tutorials

For the lecture there will be weekly tutorials. In order to write the exam at the end of the lecture, you must attend and actively participate in one of the tutorial groups. New assignments will be published here every week. In order to participate in the lecture and the tutorials, you need to register for the tutorials and apply for a spot in one of the five tutorial groups until April 11th (see below).

Participation in the tutorials will be done via the conference software Zoom. You require a microphone for presenting your solution in the online lectures. You should install the Zoom client for being able to use the annotation function and to be able to share your screen while you present your solutions. A connection test will be held on the week 12th-16th April to assure that all students are able to connect to the meeting of their respective groups. The first assignment sheet will be discussed in the tutorial in the following week.

You must prepare answers to the written assignments, which are published on this webpage every week, at home and indicate by the given deadline on the Moodle webpage of the course whether or not you are volunteering to present your solutions. During the tutorial, we will ask one of the volunteers for each of the assignments to present their prepared solutions, usually the screen should be shared during this presentation. The presented solution does not necessarily have to be completely correct, but it has to be visible that you made an honest attempt to solve the assignment and tried to overcome possible difficulties. In case we ask you to present a solution which you volunteered for, but you can not present or it is clear that you did not made a reasonable attempt to solve the assignment, the first time we will void the volunteer-point for that assignment, the second time we will void the volunteer points for the whole assignment sheet. If this happens a third time, you will not be permitted to write the final exam.

You pass the tutorial (and are allowed to write the exam) only if you volunteer for at least 2/3 of all assignments and presented a solution at least two times.

There are five tutorial groups:

In order to attend a tutorial group, you will need to apply for a spot in one of the groups. This done via the LSF system from 22nd March to 11th April. Please use this link to see the tutorial information in the LSF system. After you log in with your student account, you can register for the tutorials and give preferences for each of the five groups (Please select all the groups that fit with your schedule, and then give preferences for each of them). We will assign the free spots in the groups based on the preferences you gave for each group. Important: There is only limited space per tutorial group and we can only offer five weekly tutorial groups. Therefore, if there are too many applicants, it might be that not every applicant can attend this lecture and the tutorials. Note that the final assignment of the free spots will be done after the application deadline is over, and you will be informed via email if you can participate in this course or not, and which tutorial group you are assigned to. The links und passwords for the Zoom Meetings will be available in the Moodle course of this lecture. Please note that you can not subscribe to the Moodle course yourself, but we will register you in the course once we assign you to a tutorial group. 

Note: Each week, one assignent sheet will be discussed. You only volunteer and present for assignments in the respective week where these assignments are scheduled to be discussed. Further, you should only volunteer and present in your own tutorial group. Visiting the other tutorial groups is possible, but it should remain an exception (e.g. due to illness or other important appointments) and should be announced beforehand. You should notify your tutor about your absence beforehand. You can then attend another tutorial group in that week. Submissions via email are not possible, with the only exception being that you are ill. If you have a certificate of illness from your physician, you can also request that the respective assignment sheet will not be counted when calculating your percentage of solved assignments in the end.

Assignments will include theoretical and practical tasks, e.g. explaining and analysing certain concepts or applying methods and calculations. Programming assignments are also possible.

Assignment Sheets

• Assignments 1 (to be discussed from 19.04. to 23.04.) (Update: to be discussed from 26.04. to 30.04.)
• Assignments 2 (to be discussed from 03.05. to 07.05.)
• Assignments 3 (to be discussed from 17.05. to 21.05.)
• Assignments 4 (to be discussed from 24.05. to 28.05.)
• Assignments 5 (to be discussed from 31.05. to 04.06.)
• Assignments 6 (to be discussed from 07.06. to 11.06.) Intructions for Matlab and PlatEmo
• Mid-term Exam (to be discussed from 14.06. to 18.06.)
• Assignments 7 (to be discussed from 21.06. to 25.06.) (Update of Assignment 4 on 17.06.)
• Assignments 8 (to be discussed from 28.06. to 02.07.)
• Assignments 9 (to be discussed from 05.07. to 09.07.)

Literature

•  Deb, Kalyanmoy. Multi-Objective Optimization Using Evolutionary Algorithms, Wiley, 2001.
• Coello, Carlos A. Coello, Gary B. Lamont, and David A. Van Veldhuizen. Evolutionary algorithms for solving multi-objective problems. Vol. 5. New York: Springer, 2007.
• Miettinen, Kaisa. Nonlinear multiobjective optimization. Vol. 12. Springer Science & Business Media, 2012.
• Ehrgott, Matthias. Multicriteria optimization. Vol. 491. Springer Science & Business Media, 2005.
• Kruse, Rudolf, et al. Computational intelligence: a methodological introduction. Springer, 2016.