Advanced Materials Science Research

Muilti Objective Optimization

Multiobjective optimization considers optimization problems involving over one objective function to be optimized simultaneously. Multi objective optimization challenges exist in other areas, such as architecture, economics and logistics, where reasonable choices can be made in the face of trade-offs between two or more competing goals. For instance, designing a substitute variable may include reducing weight while optimizing strength or selecting a portfolio may include optimizing anticipated returning while minimizing the chance. Typically, there doesn't exist one solution that simultaneously optimizes each objective. Instead, there exists a (possibly infinite) set of Pareto optimal solutions. A solution is termed non-dominated or Pareto optimal if none of the target functions are often improved in value without degrading one or more of the opposite objective values. Despite additional subjective preference knowledge, all of Pareto's optimization techniques are considered equally fine. 

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