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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 61–70 of 155 papers

TitleStatusHype
Epoch-based Application of Problem-Aware Operators in a Multiobjective Memetic Algorithm for Portfolio Optimization—0
AI-Assisted Detector Design for the EIC (AID(2)E)—0
D3PG: Dirichlet DDPG for Task Partitioning and Offloading With Constrained Hybrid Action Space in Mobile-Edge Computing—0
Controllable Pareto Multi-Task Learning—0
Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables—0
Comparative Analysis of Indicators for Multiobjective Diversity Optimization—0
Common pitfalls to avoid while using multiobjective optimization in machine learning—0
Application of Particle Swarm Optimization to Microwave Tapered Microstrip Lines—0
An Analysis of Phenotypic Diversity in Multi-Solution Optimization—0
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization—0
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