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MBO

November 2, 2020

Course on Robust Policies for Operations Management Problems

This publication concerns the overview and lecture notes for the course Robust policies for operations management problems. For all other materials, please check the resources (part 1-5) and the links to the web lectures. Societal and industrial parties are facing uncertainties in demands, costs, and many more parameters on which their revenues based. So, the important question is: how companies are making decisions while many of the decision parameters are uncertain? In this resources related to this course we will learn how to answer this question from the perspective of “robustness". This is concept that helps us to make decisions that are not vulnerable to the changes in the uncertain parameters. So, most important concept that will be discussed is: Robustness in Optimization problems. Robustness is critical, especially in making strategic and tactical decisions, which are the decisions that are optimal for a long time. Furthermore, it is important to know how the companies should react to the realization of an uncertain parameter. For instance, what companies should do when the demand is known, the prices are set, the weather condition is known, and etcetera. Learning objectives: Different ways of formulating optimization problems Robust decisions methods to solve or approximate the formulated optimization problems Apply these methods to Operation Management problems and real-life cases. This course consists of 5 modules: -Module 1: Introduction and motivation 1.A: Lecture: Introduction 1.B: Lecture Motivation -Module 2: Static robust optimization 2.A: Robust Conterpart 2.B: Vertex enumeration 2.C: Robust Facility Location 2.D: Uncertainty set Selection -Module 3: Adaptive robust optimizationo What the idea behind Finite Adaptibility is and how to formulate it mathematically. 3.A: Adaptivity in optimization - Adaptive robust optimization - •Difference with (static) RO 3.B: Finitely adaptability 3.C: Affine decision rules 3.D: Finite scenario approach -Module 4: Robust optimization with integer variable 4.A: Lecture 4.B: Excercise and solutions -Module 5: Art of modeling

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Ahmadreza Marandi

November 2, 2020

Course on Robust Policies for Operations Management Problems: Module 4 - Robust Optimization with Integer Variables

In module 4 of the course on 'Robust policies for operations management problems' we focus on: robust optimization with integer variables: Learning objectives: o How to deal with integrality in Static Robust Optimization o How to deal with integrality of “here-and-now” decisions in Adaptive Robust Optimization (ARO) o How to deal with integrality of “wait-and-see” decisions in ARO o How to construct an iterative method using Voronoi diagram The materials that are provided for this module are the PPT file and the video of the lecture, as well as a worked out exercise. The material is designed for MSc students in the field of Operations Management. To understand the material, basic knowledge on linear algebra as well as linear optimization is required.

Presentation

Ahmadreza Marandi

November 2, 2020

Course on Robust Policies for Operations Management Problems: Module 3 - Adaptive Robust Optimization

In module 3 of the course on 'Robust policies for operations management problems' we focus on the following learning objectives: o What adaptivity means and how to formulate it mathematically o What differences exist between adaptive and static RO o What the idea behind Finite Adaptibility is and how to formulate it mathematically. The resources consist of the PPT's and links to all the web lectures concerning: 3.A Adaptivity in optimization - Adaptive robust optimization - •Difference with (static) RO 3.B Finitely adaptability 3.C Affine decision rules 3.D Finite scenario approach The resources consist of the PPT's and links to all the web lectures. Also included is an exercise (including solutions)

Presentation

Ahmadreza Marandi

November 2, 2020

Course on Robust Policies for Operations Management Problems: Module 2 - Static Robust Optimization

This resource concerns module 2 (Static robust optimization) of the course on 'Robust policies for operations management problems'. It includes web lectures and slides concerning the following topicsand learning objectives: 2.A: Selecting a robust counterpart o How to formulate Robust Optimization mathematically o How to reformulate it using linear programming duality 2.B: Vertex numeration and the deterministic reformulation o Drawback of using the reformulation obtained by duality o How to use vertex enumeration as an alternative technique 2.C: Robust facility location o How to construct the RC using a deterministic model o How to reformulate RC by analyzing the model o What can we get from solving RC 2.D: Dealing with a set of uncertainties o What the effect of the uncertainty set is in the solution o How we can select the parameters of an uncertainty set The material is designed for MSc students in the field of Operations Management. To understand the material, basic knowledge on linear algebra as well as linear optimization is required. There is a typo in the video of 2A. Robust Counterpart. From 38:55 onward, when we use the duality to reformulate the problem, there is a typo that is carried through the rest of the answer. The correct dual is provided in the lecture note page 8 and the final reformulation is on page 9, equation (2.14).

Presentation

Ahmadreza Marandi

November 2, 2020

Course on Robust Policies for Operations Management Problems: Module 5 - Art of Modeling

In module 5 of the course on 'Robust policies for operations management problems' we focus on: the 'Art of Modeling) Learning objectives are to understand: o How modeling affects the solution of Robust Optimization o Why we get such differences The material is designed for MSc students in the field of Operations Management. To understand the material, basic knowledge on linear algebra as well as linear optimization is required.. The resources consist of the PPT and a link the web lecture. Also included is an exercise (including solutions) The material is designed for MSc students in the field of Operations Management. To understand the material, basic knowledge on linear algebra as well as linear optimization is required.

Presentation

Ahmadreza Marandi

November 2, 2020

Course on Robust Policies for Operations Management Problems: Module 1 - Sources of Uncertainty, Probability Theory and its Limitations

This resource concerns module 1 of the course 'Robust policies for operations management problems'. The resources consist of 2 PPT's and the related web -lectures. Learning objectives Sources of uncertainty Limitation of working with average values Limitation of working with chance constraints Why we should use Robust Optimization The material is designed for MSc students in the field of Operations Management. To understand the material, basic knowledge on linear algebra as well as linear optimization is required. Note that the powerpoint version may differ slightly from the PDF version. Please consult the PDF for the original content.

Presentation

Ahmadreza Marandi

February 3, 2016

Advanced Design and Optimization of Composite Structures I

This course introduces the basic components of an airframe structure and discusses their use and limitations. The realities of composite design such as the effect of material scatter, environmental knockdowns, and damage knockdowns are discussed and guidelines accounting for these effects and leading to robust designs are presented. The resulting design constraints and predictive tools are applied to real-life design problems in composite structures. A brief revision of lamination theory and failure criteria leads into the development of analytical solutions for typical failure modes for monolithic skins (layup strength, buckling under combined loads and for a variety of boundary conditions) and stiffeners (strength, column buckling under a variety of loads and boundary conditions, local buckling or crippling for one-edge and no-edge-free conditions). These are then combined into stiffened composite structures where additional failure modes such as skin-stiffener separation are considered. Analogous treatment of sandwich skins examines buckling, wrinkling, crimping, intra-cellular buckling failure modes. Once the basic analysis and design techniques have been presented, typical designs (e.g. flange layup, stiffness, taper requirements) are presented and a series of design guidelines (stiffness mismatch minimization, symmetric and balanced layups, 10% rule, etc.) addressing layup and geometry are discussed. On the metal side, the corresponding design practices and analysis methods are presented for the more important failure modes (buckling, crippling) and comparisons to composite designs are made. A design problem is given in the end as an application of the material in this Part of the course.

Website

Christos Kassapoglou, Mostafa Abdalla

March 21, 2022

Medical Image Analysis

This course is a sequel to the image processing course (8DB00) in the TU/e bachelor program Biomedical Engineering. In the Medical Image Analysis course (8DC00), we concentrate on more advanced image analysis methods and on how they can be used to tackle clinical problems. Topics covered include image registration, computer-aided diagnosis and machine learning. The course has a very strong focus on programming (implementing medical image analysis methods) in Python and relies on previous knowledge of calculus and linear algebra.

Website

Maureen Eijnatten, van, Mitko Veta, Veronika Cheplygina, Daniel Krahulec, Evi M.C . Huijben

December 1, 2025

Practice Material for Fundamental Courses in Economics

The repository is designed as an open, collaborative collection of digital exercises and supplementary teaching materials for fundamental economics courses. It is structured into subjects that are often found in economics courses. These subjects allow teachers to identify and integrate those exercises they need, based on the topics they are interested in. All exercises are available in English and Dutch. Selected exercises can be implemented through the Grasple platform directly with a free teacher account. Thematic Exercise Sets Basic Microeconomics: Exercises covering cost concepts, elasticity, optimization, and static market theory. Intermediate Microeconomics: Exercises addressing topics such as asymmetric information, principal-agent problems, and externalities. Mathematics in Economics: Materials that bridge mathematical techniques (like differential equations and linear algebra) with economic applications, created in collaboration with the department of Applied Mathematics at TU Delft. Open Educational Practices

Website

Sander Renes, Tom Vroegrijk, Daniela Petrova

April 22, 2024

From theORy to application: learning to optimize with Operations Research in an interactive way

This book serves as a comprehensive roadmap for navigating the realm of Operations Research (OR). From laying down fundamental mathematical principles to crafting precise modeling techniques and their solution methods, it culminates in a panoramic view of OR models mirroring real-world operations. Delving into diverse applications-from assignment problems to network problems like graph coloring and minimum spanning trees, and navigating through routing problems that are very common in logistics-the book equips readers with practical insights. Each model is accompanied by meticulously detailed examples, seamlessly integrated with hyperlinked codes accessible via an open repository. Moreover, it introduces an engaging dimension with hyperlinks to three serious games replicating some cornerstone OR models, offering a playful yet educational environment for solo or group experimentation.

Open (Access) Text Book

Alessandro Bombelli, Bilge Atasoy, Stefano Fazi, Doris Boschma