Abstract
A new efficient heuristic algorithm has been developed for the dynamic facility layout problem with budget constraint (DFLPB) using optimization via simulation technique. The heuristic integrates integer programming and discrete event simulation to address DFLPB. In the proposed algorithm, the nonlinear model of the DFLP has been changed to a pure integer programming (PIP) model. Then, the optimal solution of the PIP model has been used in a simulation model that has been designed in a similar manner as the DFLP for determining the probability of assigning a facility to a location. After a sufficient number of runs, the simulation model obtains near optimum solutions. Finally, to test the performance of the algorithm, several test problems have been taken from the literature and solved. The results show that the proposed algorithm is more efficient in terms of speed and accuracy than other heuristic algorithms presented in previous works.
Highlights
According to [1], the problem associated with the placement of facilities in a plant area, often referred to as the “facility layout problem,” is known to have a significant impact on manufacturing costs, work in processes, lead times, and company productivity
All constraints have been coded using Enterprise Dynamics 8.1 software with 4D Script language. All input parameters such as the rearrangements costs, material handling costs, and the optimal solutions of Problem 2 are stored in tables within the software, and when the software assigns a facility to a location at each period, the related costs will be stored in another table that calculates the objective function of Problem 1 at the end of each run
The percentage of deviation, denoted by “%Dev.” of the best solution obtained from the proposed algorithm, which is lower than the best solution obtained from [26], is given in the eighth column, for each test problem
Summary
According to [1], the problem associated with the placement of facilities in a plant area, often referred to as the “facility layout problem,” is known to have a significant impact on manufacturing costs, work in processes, lead times, and company productivity. Rosenblatt [8] showed the first research to develop an optimization approach based on a dynamic programming model for the DFLP. Erel et al [15] introduced a new heuristic algorithm to solve the DFLP They used weighted flow data from various time periods to develop viable layouts and suggested the shortest path for solving the DFLP. The last one, which is the newest related research, used a budget constraint for each period separately They developed a simulated annealing algorithm for the problem and showed that their algorithm is more efficient than the two previous researches. They used the optimal solution of their linear model as a probability distribution in a simulation model While they used this approach toward solving the traveling salesman problem, this empirical distribution can be used here to determine the probability of assigning facilities to certain locations.
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