A Genetic Algorithm for the Unequal Area Facility Layout Problem

Abstract

Unequal Area Facility Layout Problem (UA-FLP) is a relevant problem with industrial application and it has been addressed by several methods having into account only quantitative criteria. This contribution presents an approach to consider subjective features in UA-FLP. An Interactive Genetic Algorithm (IGA) is proposed that allows interaction between the algorithm and the Decision Maker (DM). The participation of the DM knowledge into the approach guides the search process, adjusting it to the DM’s preferences at every iteration of the algorithm. The whole population is evaluated by the DM through subjective evaluation of the represen- tative individuals. In order to choose this individuals, a soft computing clustering method is used. The empirical evaluation shows that the proposed IGA is capable of capturing DM preferences and it can progress towards a good solution in a rea- sonable number of iterations to avoid the user tiredness.