https://github.com/marialaurasantoni/diversity-fitness
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
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Multi-objective optimization (also known as multi-objective programming, vector optimization, multicriteria 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, respectively. In practical problems, there can be more than three objectives.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.