Multi-Objective Light Ray Optimization
Abstract
Recommendations
Multi-objective optimization using teaching-learning-based optimization algorithm
Two major goals in multi-objective optimization are to obtain a set of nondominated solutions as closely as possible to the true Pareto front (PF) and maintain a well-distributed solution set along the Pareto front. In this paper, we propose a teaching-...
Inverted PBI in MOEA/D and its impact on the search performance on multi and many-objective optimization
GECCO '14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary ComputationMOEA/D decomposes a multi-objective optimization problem into a number of single objective optimization problems. Each single objective optimization problem is defined by a scalarizing function using a weight vector. In MOEA/D, there are several ...
Multimodal scalarized preferences in multi-objective optimization
GECCO '17: Proceedings of the Genetic and Evolutionary Computation ConferenceScalarization functions represent preferences in multi-objective optimization by mapping the vector of objectives to a single real value. Optimization techniques using scalarized preferences mainly focus on obtaining only a single global preference ...
Comments
Information & Contributors
Information
Published In
Publisher
IEEE Computer Society
United States
Publication History
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Other Metrics
Citations
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in