Multi Objective and Genetic Algorithm to Distribute the Jobs to the Workers at the Assembly Line

Automobile manufacturing is one of the most important industries in the world. The Production Line (PL) is one of the main supply chain of this industry. The PL contains several shops and stations to complete the product. The number of workers is one variable at PL, the workers need time to weld the pieces to the structure of the car. The cycle times stations not equal in each station and shop. The unbalance cycle time stations create queuing and idle time. The Production Line Balancing Problem (PLBP) is one of the main focuses on research in automobile manufacturing. The problem in PLBP is the queuing and the idle time during task achievement that is an obstacle to efficient assembly line. Moreover, the unbalancing problems also include the number of workers among the stations. This study used a new method to solve these problems. The new method is the Multi-Objectives Model (MOM) combined with the Genetic Algorithm system (GAs). This approach is employed to solve the production line problems and to develop the efficiency of the production line. As a result, the Mixed Model combines the MOM and GA is developed to solve the PLBP and efficiency of the Production Line System (PLS) in order to reduce the queuing and the idle time to obtain the best balance among the stations through to re-distribute the jobs to the workers among the stations in order to obtain the optimum solution