An optimization method for the facility layout problem using a real-coded genetic algorithm

Most of the algorithms for the facility layout problem (FLP) attempt to solve the problem through encoding layout candidates and using combinational optimization techniques to obtain the best encoded candidates. However, since FLP is a continuous optimization problem by nature, layouts exist which cannot be represented by these encoding techniques. Therefore, there is possibility that the opportunity to search for the optimal solution will be missed. Furthermore, some algorithms attempt to solve FLP as a continuous problem; however, since FLP is a non-convex problem, it is known that these algorithms have the problem of being trapped into local optima. To overcome these problems, this paper proposes an algorithm to solve FLP through applying a real coded genetic algorithm (RCGA), which is known to be effective for many types of continuous optimization problems.