A modified objective function method with feasible-guiding strategy to solve constrained multi-objective optimization problems.
Licheng JiaoJuanjuan LuoRonghua ShangFang LiuPublished in: Appl. Soft Comput. (2014)
Keyphrases
- objective function
- high accuracy
- cost function
- detection method
- experimental evaluation
- computational cost
- high precision
- computationally efficient
- constrained optimization
- search strategy
- feasible solution
- data sets
- linear programming
- optimization algorithm
- edge detection
- greedy algorithm
- classification method
- least squares
- scheduling problem
- multi objective
- computational complexity
- image segmentation