Multi-objective optimization (also known as multi-objective programming, vector optimization, multiattribute optimization, or Pareto optimization) is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective optimization has been applied in many fields of science, including engineering, economics, and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives. Minimizing cost while maximizing comfort while buying a car and maximizing performance whilst minimizing fuel consumption and emission of pollutants of a vehicle are examples of multi-objective optimization problems involving two and three objectives. In practical problems, there can be more than three objectives.
SPEAKER: Eyal Kazin
EVENT: PyData Eindhoven 2021
CREDITS: PyData YouTube channel : / @pydatatv
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