Name
Abstract | ||
|---|---|---|
This paper presents a hybrid system for incorporating human expert knowledge into the unequal area facility layout problem. A subset of facility designs is generated using a genetic algorithm and then evaluated by a human expert. The hybrid system consists of assigning a mark, where the principal aim is to substitute the human expert's knowledge to avoid fatiguing or burdening him or her. The novel proposed approach was tested using a real case study of 365 facility layout designs for an ovine slaughterhouse. The validation phase of the intelligent model presented was performed using a new subset of 181 facility layout designs evaluated by a different human expert. The results of the experiment, which validate the proposed approach, are presented and discussed in this study. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.neucom.2013.01.068 | Neurocomputing |
Keywords | Field | DocType |
Evolutionary Computation,Artificial neural networks,Unequal area facility layout problem,Genetic algorithm,Heuristic search | Heuristic,Facility layout problem,Evolutionary computation,Neural system,Facility layout,Artificial intelligence,Artificial neural network,Hybrid system,Mathematics,Genetic algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
135 | C | 0925-2312 |
Citations | PageRank | References |
4 | 0.39 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura García-Hernández | 1 | 54 | 8.81 |
| M. Pérez-Ortiz | 2 | 13 | 3.24 |
| Antonio Arauzo | 3 | 122 | 11.71 |
| Lorenzo Salas-Morera | 4 | 51 | 7.79 |
| César Hervás-Martínez | 5 | 796 | 78.92 |