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Optimization

CM_Opti MSE Course (lecture 1)

CM_Opti MSE Course (lecture 1)

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Kartei Details

Karten 9
Sprache Deutsch
Kategorie Mathematik
Stufe Universität
Erstellt / Aktualisiert 06.06.2021 / 06.06.2021
Lizenzierung Keine Angabe
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https://card2brain.ch/box/20210606_optimization
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Which two main areas of application exist in optimization?

  1. Optimization of business processes (production, logistics, services, operations management, ...) -> main focus in course:
    1. Optimize aircraft assignment in flight operations
    2. Optimize production planning in complex manufacturing plants
    3. Optimize machine utilizatino in shop floor scheduling
  2. Optimization of technical processes (engineering):
    1. Optimize machining conditions in metal-cutting (speed, pressure, angle, ...)
    2. Optimize parameters of chemical or physical experiments

What is the difference betwen qualitative vs. quntitative optimization?

  • Quantitative analysis and optimization:
    • Bases of quantifiable information and knowledge:
      • Numerical, measurable data, mathematical models and algorithms
  • Qualitative analysis and optimization
    • Bases on non-quantifiable information and knowledge:
      • "informal" facts, verbal descriptions of processes and procedures, unstructered information, experience, implicit know-how
  • Example of typically quantitative optimization problems:
    • Finding "the best" equipment (machines, tools, etc.) for a cerain task
    • Finding "optimal" locations for facilities (plants, warehouses, ...) in a supply network
    • Improving business processes

 

What do we typically have in Business Consulting projects?

  • Phase 1: Qualitative analysis (very important, often up to 80%)
    • Often unclear problem descriptions, mess of information, contradictory opinions
  • Phse 2:
    • Either qualitative improvements: e.g. definition and implementation of new processes
    • Or quantitative, e.g.:
      • Identification of certain subsystems crucial for performance
      • Having quantitative characteristics, not solvable by "common sense" (intuition, ...)
      • Need for "decision support" fromo methematical models

 

What should you alway remember when working on optimizatin problems?

  • In general, before applying quantitative methos:
    • Huge amount of challenging and crucial prelininary qualitative work is necessary:
      • Finding out, what the real problem is, defining scope and project boundaries, ...
      • Understanding all necessary details of the business areas involved, ...
      • Often this is the most difficult part of the project
      • Solving the wrong problem or solving the right problem inadequately
      • Qualitative analysis and initial, conceptual design crucial for project success
      • Often more challenging than development of quantitative methods
      • Matter of experience, intuition, dialogue with business partners