Abstract
Multiobjective optimization (also known as multiobjective programming, vector optimization, multicriteria optimization, multiattribute optimization, or Pareto optimization) is an area of multiple-criteria decision-making, concerning mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multiobjective optimization has been applied to many fields of science, including engineering, where optimal decisions need to be taken in the presence of trade-offs between two or more objectives that may be in conflict. Indeed, in many practical engineering applications, designers are making decisions between conflict objectives—for example, maximizing performance while minimizing fuel consumption and emission of pollutants of a vehicle. In these cases, a multiobjective optimization study should be performed, which provides multiple solutions representing the trade-offs among the objective functions.
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