Handling Qualitative Aspects in Unequal Area Facility Layout Problem: A Novel Multi-Criteria Decision-Making Model.

The unequal area facility layout problem (UA-FLP) has been addressed by many approaches. Most of them only consider quantitative aspects into the approach. In this work, we will solve UA-FLPs using a novel hybrid model that joins multi-criteria decision making method and interactive evolutionary optimization. Particularly, a combination of the analytic hierarchy process (AHP) and an interactive genetic algorithm, is suggested. By means of this new model, it is possible to take into account both qualitative (using the expert knowledge) criteria and quantitative in order to achieve an acceptable design solution. Our algorithm is able to interact with the decision maker (DM), directing the search process by means of the DM preferences and arranging the criteria that are more important in each design solution. Thus, the system is adapted to the DM's preferences by means of his/her subjective evaluations of the designs that are consider as representative of the population (reached by a clustering method), and also, to the quantitative criteria. In order to test the proposed approach, an interesting real-world data set has been probed and analysed. Important results are achieved, and relevant conclusions are drawn from the application of this novel intelligent framework.