Optimal Solution for Multi-Objective Facility Layout Problem Using Genetic Algorithm

This paper addresses optimization of multi-objective facility layout problem. Facility layout plays a key role for companies, and it is an inseparable part of the manufacturing system design process. Traditionally there are two approaches to the facility layout problem. One is the quantitative approach aiming at minimizing the total material handling cost and another is qualitative approach aiming at maximizing closeness rating score. In this paper both approaches have been taken into consideration separately. Again, the research also solved the problem combining these two approaches at the objective function level. Genetic algorithm (GA) is developed for the multi-objective facility layout problem and found out the optimal facility location for a particular problem considering the two objectives, i.e. minimization of the material handling cost and maximization of the closeness rating score. In GA, primarily an initial population is created and by the crossover operator and mutation process new offspring is generated and if the offspring meet the stopping criteria the result was selected for the process. From this approach, a non dominated solution set is found (Pareto optimal) approximately for the multi objective facility layout problem.