Using Multi-objective Ant Colony Optimization Algorithm to Solve a Multi-obj ective Facility Layout Problem in Dynamic Cellular Manufacturing

In cellular production, the production system is aimed at transforming several subsystems into a cell in order to produce similar products in a cell with a higher efficiency. In this paper, a multi-objective model in the layout-routing problem of cell production with the goal of minimizing costs, maximizing the level of service to customers has been addressed and solved using the meta- heuristic algorithm MOACO. The results of solving a bi-objective model using this meta-heuristic algorithm with its results in its previous solution method, the meta-heuristic algorithm NSGAII and the Epsilon constraint method showed that MOACO is able to provide better responses than NSGAII for large-scale issues. That is, at approximately equal times, algorithm MOACO was able to produce more accurate and better answers for the second objective function.

Keywords:

Cellular Production , Multi-objective Model , Meta Heuristic Algorithms , MOACO , NSGAII , Epsilon Constraint