Optimization of a Production System Using Search Method

The Kanban production authorization system has been widely implemented as a control scheme for justin-time manufacturing. This system is normally applied in systems with reliable process, low setup time, static demand and excess capacity. The use of Kanban avoids the need for complex information and hierarchical control systems on the shop floor. In the present work Genetic Algorithm (GA) approach is used to set number of Kanbans and lot sizes at each station to achieve best performance of the system. Productivity of the approach is studied in term of a predefined achieved performance value and CPU time which is an important factor to evaluate an algorithm. System objective is derived by an experiment and it includes minimizing average Kanban lot queue and maximizing mean throughput rate. Although GA is not developed for optimization problem and it is not guaranteed that GA gives global optimum, but it is successful in finding a satisfactory solution for the practical problem, while CPU time used by GA is much less than many other optimization methods. KeywordsGenetic Algorithm , Just in time, Optimization.