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      Optimization methods for industry

      Many of the problems that exist in industry can be formulated as optimization problems and tackled with various optimization methods seeking the best alternative(s) for decision making. In fact, almost every product, process or system has the potential to be improved so the applications for optimization are countless. In the case of industrial problems, optimization is very often about maximizing profit, productivity, efficiency and quality while minimizing time, cost, waste and risk.

      There are many exciting new developments in research and industrial practice alike when it comes to various optimization methods, and these include classical linear programming as well as modern meta-heuristic and simulation-based algorithms. This course covers some fundamental theories of optimization and then provides the student with the requisite knowledge to select and apply various optimization methods and software tools to solve industrial-scale problems.

      Learn a range of optimization methods

      The course is taught via lectures, laboratory (hands-on) exercises and project work. The course covers the following topics: classical optimization methodologies and standard optimization models, metaheuristic algorithms for solving single and multi-objective optimization problems, simulation-based optimization and its industrial applications, the industrial applications of optimization, and decision analysis.

      Who is the course for?

      The course targets industrial professionals, especially engineers, who want to learn more about how to use a range of optimization methods to optimize processes and systems in their industry.

      After completing the course, you will be able to:

      • Demonstrate a good understanding of different types of optimization techniques, including classical, metaheuristic and simulation-based methods
      • Formulate optimization problems based on industrial scenarios and relate them to standard optimization models
      • Suggest appropriate optimization methods for a variety of industrial applications
      • Apply software available to industry to solve optimization problems.

      Entry requirements:

      The entry requirements for this course are a Bachelor’s degree of at least 180 higher education credits (equivalent to 180 ECTS) within the field of integrated product development or production engineering or automation engineering or mechanical engineering or information technology or a similar field, and a minimum of 12 months of documented work experience in a relevant domain.

      If you do not fulfill these higher education requirements, you can apply to be assessed based on your work experience. You can use the skills description template to describe your work experience.

      Practical information:

      • Course period: Week 6 - Week 15 2020
      • Rate of study: 25%
      • Applications are open until 2 weeks before the course starts. 
      • Course Syllabus

      Application Information:

      Kontakt

      Associate Professor of Production Engineering

      Professor of Automation Engineering

      Associate Professor of Production Engineering

      Published: 3/2/2020
      Edited: 3/2/2020
      Responsible: webmaster@his.se