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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 151155 of 155 papers

TitleStatusHype
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization0
Common pitfalls to avoid while using multiobjective optimization in machine learning0
Comparative Analysis of Indicators for Multiobjective Diversity Optimization0
Controllable Pareto Multi-Task Learning0
D3PG: Dirichlet DDPG for Task Partitioning and Offloading With Constrained Hybrid Action Space in Mobile-Edge Computing0
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