Name
Title | ||
|---|---|---|
A new penalty function method for constrained optimization using harmony search algorithm |
Abstract | ||
|---|---|---|
This paper proposes a novel penalty function measure for constrained optimization using a new harmony search algorithm. In the proposed algorithm, a two-stage penalty is applied to the infeasible solutions. In the first stage, the algorithm can search for feasible solutions with better objective values efficiently. In the second stage, the algorithm can take full advantage of the information contained in infeasible individuals and avoid trapping in local optimum. In addition, for adapting to this method, a new harmony search algorithm is presented, which can keep a balance between exploration and exploitation in the evolution process. Numerical results of 13 benchmark problems show that the proposed algorithm performs more effectively than the ordinary methods for constrained optimization problems. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CEC.2014.6900375 | IEEE Congress on Evolutionary Computation |
Keywords | Field | DocType |
optimisation,benchmark problems,harmony search algorithm,penalty function method,search problems,evolution process,constrained optimization problems,two-stage penalty,optimization,vectors,nickel,linear programming,algorithm design and analysis | Min-conflicts algorithm,Computer science,Augmented Lagrangian method,Artificial intelligence,Metaheuristic,Mathematical optimization,Local optimum,Algorithm,Harmony search,Constrained optimization problem,Machine learning,Constrained optimization,Penalty method | Conference |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Biao Zhang | 1 | 60 | 8.85 |
| Jun-Hua Duan | 2 | 65 | 3.96 |
| Hong-yan Sang | 3 | 165 | 11.18 |
| Junqing Li | 4 | 462 | 42.69 |
| Hui Yan | 5 | 2 | 2.05 |