A novel hybrid multi-criteria decision-making model to solve UA-FLP

Abstract

The unequal area facility layout problem (UA-FLP) has been addressed by many approaches. Most of them only take quantitative aspects into consideration. In this paper, we will solve UA-FLP using a novel hybrid methodology that joins interactive evolutionary optimization and multi-criteria decision making. I particular, a combination of an interactive genetic algorithm and the analytic hierarchy process (AHP), is proposed. By means of this new approach, it is possible to consider both quantitative and qualitative (using the expert knowledge) criteria in order to reach an acceptable design. Our approach allows the decision maker (DM) to interact with the algorithm, guiding the search process and ranking the criteria that are more relevant in each design solution. In this way, the algorithm is adjusted to the DM’s preferences through his/her subjective evaluations of the representative solutions obtained by a clustering method, and also, to the quantitative criteria. A interesting real-world data set is analysed to empirically probe the robustness of this model. Relevant results are obtained, and interesting conclusions are drawn from the application of this novel intelligent framework.