Search result: Catalogue data in Autumn Semester 2021

Geospatial Engineering Bachelor Information
Compulsory Courses
Examination Block 3
NumberTitleTypeECTSHoursLecturers
363-1004-00LOperations ResearchO3 credits2GS. Bütikofer van Oordt
AbstractThis course provides an introduction to operations research methods in the fields of management science and economics. Requisite mathematical concepts are introduced with a practical, problem-solving perspective.
Objective- Introduction to building and using quantitative models in a business / industrial environment
- Introduction to basic optimization techniques (Linear Programming and extensions, network flows, integer programming, dynamic and stochastic optimization)
- Understanding the integration of quantitative models into the managerial decision process
ContentThe economic environment of today's companies is characterized by high cost pressure, declining margins, intensified international competition, rising customer requirements and increasingly strict regulations. Strategic and operational decisions at all management levels are becoming more and more complex due to the increasing amount of data, interrelationships, conditions and target criteria to be considered. Often it is no longer possible to solve operational tasks with experience and common sense alone and to adequately estimate the consequences of decisions without software support.

Quantitative models and methods of operations research and operations management offer decision support for complex problems. Mathematical optimization models are used to precisely formulate operational decision problems so that they can subsequently be analysed and optimized using suitable solution methods. A large number of quantitative real-world problems can be formulated and solved in this general framework. Applications of operations research comprise, for instance, decision problems in production planning, supply chain management, transportation networks, machine and workforce scheduling, blending of components, telecommunication network design, airline fleet assignment and revenue management.

This course offers an introduction to operations research, emphasizing basic methodologies and underlying mathematical structures. The following topics are covered in detail:
- Introduction to system modelling and operations research
- Linear models and the importance of linear programming
- Duality theory in linear programming and shadow prices
- Integer programming
- Dynamic optimization (under uncertainty) and applications in inventory management.
Lecture notesA printed script will be made available.
LiteratureAny standard textbook in Operations Research is a useful complement to the course.
Prerequisites / NoticeUndergraduate calculus, linear algebra, probability and statistics are a prerequisite.
101-0031-01LSystems EngineeringO4 credits4GB. T. Adey
Abstract• Systems Engineering is a way of thinking that helps engineer sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long terms.
• This course provides an overview of the main principles of Systems Engineering, and includes an introduction to the use of operations research methods in the determination of optimal systems.
ObjectiveThe world’s growing population, changing demographics, and changing climate pose formidable challenges to humanity’s ability to live sustainably. Ensuring that humanity can live sustainably requires accommodating Earth’s growing and changing population through the provision and operation of a sustainable and resilient built environment. This requires ensuring excellent decision-making as to how the built environment is constructed and modified.

The objective of this course is to ensure the best possible decision making when engineering sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long term. In this course, you will learn the main principles of Systems Engineering that can help you from the first idea that a system may not meet expectations, to the quantitative and qualitative evaluation of possible system modifications. Additionally, the course includes an introduction to the use of operations research methods in the determination of optimal solutions in complex systems.

More specifically upon completion of the course, you will have gained insight into:
• how to structure the large amount of information that is often associated with attempting to modify complex systems
• how to set goals and define constraints in the engineering of complex systems
• how to generate possible solutions to complex problems in ways that limit exceedingly narrow thinking
• how to compare multiple possible solutions over time with differences in the temporal distribution of costs and benefits and uncertainty as to what might happen in the future
• how to assess values of benefits to stakeholders that are not in monetary units
• how to assess whether it is worth obtaining more information in determining optimal solution
• how to take a step back from the numbers and qualitatively evaluate the possible solutions in light of the bigger picture
• the basics of operations research and how it can be used to determine optimal solutions to complex problems, including linear, integer and network programming, dealing with multiple objectives and conducting sensitivity analyses.
ContentThe weekly lectures are structured as follows:
1 Introduction – An introduction to System Engineering, a way of thinking that helps to engineer sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long terms. A high-level overview of the main principles of System Engineering. An introduction to the example that we will be working with through most of the course. The expectations of your efforts throughout the semester.
2 Situation analysis – How to structure the large amount of information that is often associated with attempting to modify complex systems.
3 Goals and constraints – How to set goals and constraints to identify the best solutions as clearly as possible.
4 Generation of possible solutions – How to generate possible solutions to problems, considering multiple stakeholders.
5 Analysis – 1/5 – The principles of net-benefit maximization and a series of methods that range from qualitative and approximate to quantitative and exact, including pairwise comparison, elimination, display, weighting, and expected value.
6 Analysis – 2/5 – The idea behind the supply and demand curves and revealed preference methods.
7 Analysis – 3/5 – The concept of equivalence, including the time value of money, interest, life times and terminal values.
8 Analysis – 4/5 – The relationship between net-benefit and the benefit-cost ratio. How incremental cost benefit analysis can be used to determine the maximum net benefit. Marginal rates of return and internal rates of return.
9 Analysis – 5/5 – How to consider multiple possible futures and use simple rules to help pick optimal solutions and to determine the value of more information.
10 Evaluation of solutions – Regardless how sophisticated an analysis is, it requires that decision makers stand back and critically evaluate the results. This week we discuss the aspects of evaluating the results of an analysis.
11 Operations research – 1/4 – Once quantitative analysis is used it becomes possible to use operations research methods to analyse large numbers of possible solutions. This week we discuss linear programming and the simplex method.
12 Operations research – 2/4 – How sensitivity analysis is conducted using linear programming.
13 Operations research – 3/4 – How to use operations research to solve problems that consist of discrete values, as well as how to exploit the structure of networks to find optimal solutions to network problems.
14 Operations research – 4/4 – How to set up and solve problems when there are multiple objectives.

The course uses a combination of qualitative and quantitative approaches. The quantitative analyses requires the use of Excel. An introduction to Excel will be provided in one of the help sessions.
Lecture notes• The lecture materials consist of a script, the slides and example calculations in Excel.
• The lecture materials will be distributed via Moodle two days before each lecture.
LiteratureAppropriate literature in addition to the lecture materials will be handed out when required via Moodle.
Prerequisites / NoticeThis course has no prerequisites.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingfostered
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
101-0515-00LProject ManagementO2 credits2GC. G. C. Marxt
AbstractThe course gives a detailed introduction on various aspects of professional project management out of theory and practice. Established concepts and methods for project organization, planning, execution and evaluation are introduced and major challenges discussed. The course includes an introduction on specialized project management software as well as agile project management concepts.
ObjectiveProjects are not only the base of work in modern enterprises but also the primary type of cooperation with customers. Students of ETH will often work in or manage projects in the course of their career. Good project management knowledge is not only a guarantee for individual, but also for company wide success.

The goal of this course is to give a detailed introduction into project management. The students should learn to plan and execute a project.
ContentProject planning (aims, appointments, capacities, efforts and costs), project organization, scheduling and risk analysis, project execution, supervision and control, project evaluation, termination and documentation, conflict management, multinational project management, IT support as well as agile project management methods such as SCRUM.
Lecture notesNo.
The lecture slides and other additional material will be available for download from Moodle a week before each class.
  •  Page  1  of  1