A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding

This paper proposes a new multi objective genetic algorithm (MOGA) for solving unequal area facility layout problems (UA-FLPs). The genetic algorithm suggested is based upon the slicing structure where the relative locations of the facilities on the floor are represented by a location matrix encoded in two chromosomes. A block layout is constructed by partitioning the floor into a set of rectangular blocks using guillotine cuts satisfying the areas requirements of the departments. The procedure takes into account four objective functions (material handling costs, aspect ratio, closeness and distance requests) by means of a Pareto based evolutionary approach. The main advantage of the proposed formulation, with respect to existing referenced approaches (e.g. bay structure), is that the search space is considerably wide and the practicability of the layout designs is preserved, thus improving the quality of the solutions obtained.

► We suggest a genetic algorithm for solving Unequal area facility Layout problems.
► The proposed algorithm is based upon the Slicing structure approach.
► We take into account four objective functions by means of a Pareto based approach.
► The search space is wide and the practicability of the layout designs is preserved.
► The solutions have been compared with those obtained using the bay structure approach.