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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 111120 of 155 papers

TitleStatusHype
Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights and Algorithms0
Pareto Multi-Task LearningCode0
Deep Innovation Protection: Confronting the Credit Assignment Problem in Training Heterogeneous Neural ArchitecturesCode0
Max-value Entropy Search for Multi-Objective Bayesian OptimizationCode1
Deep Innovation Protection0
Pareto-optimal data compression for binary classification tasksCode0
Pareto Optimal Demand Response Based on Energy Costs and Load Factor in Smart Grid0
ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without RetrainingCode1
Scalarizing Functions in Bayesian Multiobjective Optimization0
Tuning metaheuristics by sequential optimization of regression models0
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