Name
Title | ||
|---|---|---|
Hybridizing A Fuzzy Multi-Response Taguchi Optimization Algorithm With Artificial Neural Networks To Solve Standard Ready-Mixed Concrete Optimization Problems |
Abstract | ||
|---|---|---|
In this study, a fuzzy multi-response standard ready-mixed concrete (SRMC) optimization problem is addressed. This problem includes two conflicting quality optimization objectives. One of these objectives is to minimize the production cost. The other objective is to assign the optimal parameter set of SRMC's ingredient to each activity. To solve this problem, a hybrid fuzzy multi-response optimization and artificial neural network (ANN) algorithm is developed. The ANN algorithm is integrated into the multi-response SRMC optimization framework to predict and improve the quality of SRMC. The results show that fuzzy multi-response optimization model is more effective than crisp multi-response optimization model according to final production cost. However, the ANN model also gave more accurate results than the fuzzy model considering the regression analysis results. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1080/18756891.2016.1175816 | INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS |
Keywords | Field | DocType |
Standard ready-mixed concrete, Multi-response optimization, Taguchi method, Fuzzy TOPSIS, Artificial neural networks | Ready mixed concrete,Neuro-fuzzy,Mathematical optimization,Regression analysis,Fuzzy logic,Taguchi methods,Artificial intelligence,Optimization algorithm,Artificial neural network,Optimization problem,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
9 | 3 | 1875-6891 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baris Simsek | 1 | 0 | 0.34 |
| Yusuf Tansel İÇ | 2 | 55 | 7.61 |
| Emir Hüseyin Simsek | 3 | 0 | 0.34 |