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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 141150 of 155 papers

TitleStatusHype
Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment methodCode0
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve OptimizationCode0
Pareto Multi-Task LearningCode0
Pareto-optimal data compression for binary classification tasksCode0
Using Traceless Genetic Programming for Solving Multiobjective Optimization ProblemsCode0
Bayesian Inverse Transfer in Evolutionary Multiobjective OptimizationCode0
QoS-aware Big Service Composition using Distributed Co-Evolutionary AlgorithmCode0
A multiobjective continuation method to compute the regularization path of deep neural networksCode0
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and SparsityCode0
Evolutionary Multiparty Distance MinimizationCode0
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