An evolutionary neural system for incorporating expert knowledge into the UA-FLP

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.