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Multiobjective Optimization

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.

Papers

Showing 3140 of 155 papers

TitleStatusHype
Efficient and Sparse Neural Networks by Pruning Weights in a Multiobjective Learning ApproachCode0
Evolutionary Multiparty Distance MinimizationCode0
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve OptimizationCode0
A multiobjective continuation method to compute the regularization path of deep neural networksCode0
Development of a machine learning-based design optimization method for crashworthiness analysisCode0
Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment methodCode0
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box SettingCode0
Explainable Bayesian OptimizationCode0
Balancing Common Treatment and Epidemic Control in Medical Procurement during COVID-19: Transform-and-Divide Evolutionary Optimization0
Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms0
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