An Evolutionary Neural System for incorporating Human Expert Knowledge into the UA-FLP
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- Research areas:
- Year:
- 2014
- Type of Publication:
- Article
- Keywords:
- Evolutionary Computation, Artificial Neural Networks, Unequal Area Facility Layout Problem, Layout Representation, Basis functions
- Authors:
-
- García-Hernández, L.
- Pérez-Ortiz, María
- Araúzo-Azofra, A.
- Salas-Morera, L.
- Hervás-Martínez, César
- Journal:
- Neurocomputing
- Volume:
- 135
- Pages:
- 69-78
- Month:
- July
- ISSN:
- 0925-2312
- BibTex:
- Note:
- JCR(2014): 2.083 Position: 36/124 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
- Abstract:
- This paper presents an hybrid system for incorporating human expert knowledge into the Unequal Area Facility Layout Problem. For that matter, a subset of facility designs are generated (using a Genetic Algorithm) and then, evaluated by an human expert. The hybrid system is giving a mark, with the aim of substituting the human expert knowledge, avoiding his/her fatigue and burden. The novel proposed approach was tested under a real case study made of 365 facility layout designs from an ovine slaughterhouse. The validation phase of the intelligent model presented is performed by means of a new subset of 181 facility layout designs with the evaluation provided by a different human expert. The results of the experiment, which validate the performance of the proposed approach, are presented and discussed in this study.
- Comments:
- JCR(2014): 2.083 Position: 36/124 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE