Unequal-area capability-based facility layout design problem with a heuristic decomposition-based iterative mathematical programming approach

Abstract

Thus far in the available literature, capability-based facility layout design approaches were developed by only considering equal machine areas, where they are assigned to the pre-specified locations. Based on this motivation, this paper introduces a new unequal-area capability-based facility layout design (UA-CBFLD) problem for the first time in the literature. In addition to the machines’ unequal-area requirements, the proper distribution of their processing capabilities over the shop floor is considered. First, a new mixed-integer non-linear programming (MINLP) model is developed. Then, a polyhedral inner-approximation method is applied to cope with non-linear area constraints. Due to its NP-hard nature and highly non-linear structure, a heuristic decomposition-based iterative solution approach is also proposed to solve realistic size problems within a reasonable time. In order to show the validity and applicability of the proposed approach, both an illustrative example with different machine-capability overlaps and a real-life application in a manufacturing company are presented. The computational results have shown that the proposed approach has found a 33.25% better layout score (as a function of the distance and the amounts of product flows) and achieved this solution 116.64% faster than the solution of the developed MINLP model via Gurobi’s standard non-linear programming solver. Furthermore, when compared to the existing cellular facility layout design of the manufacturing company, the proposed capability-based unequal-area layout design option has also 29.37% and 34.74% superior layout scores under the scenarios of equal and unequal machine areas, respectively. Moreover, the total average machine utilization has increased up to 89.6%, which is comparatively better than the current average cell utilization, i.e., 65.2%.