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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

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Showing 81–90 of 155 papers

TitleStatusHype
Two novel feature selection algorithms based on crowding distance—0
An Analysis of Phenotypic Diversity in Multi-Solution Optimization—0
Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization ProblemsCode1
Heterogeneous Objectives: State-of-the-Art and Future Research—0
An Online Prediction Approach Based on Incremental Support Vector Machine for Dynamic Multiobjective Optimization—0
End-to-end deep meta modelling to calibrate and optimize energy consumption and comfortCode1
ES-ENAS: Efficient Evolutionary Optimization for Large Hybrid Search SpacesCode0
Manifold Interpolation for Large-Scale Multi-Objective Optimization via Generative Adversarial Networks—0
Using BART to Perform Pareto Optimization and Quantify its Uncertainties—0
On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation—0
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