Literature review and historical context

Assembly Line Balancing is a crucial step in the production line for vehicle manufacturers, and it takes time. It is one of the trickier optimization challenges and a fundamental issue in continuous manufacturing lines. The task allocation stations found in (ALB) are numerous, and each station has a number of activities that help to complete the job work. The fundamental issue with the Assembly Line Balancing is the congestion between stations as tasks are completed, which interferes with an effective assembly line. In this research, the queuing problem will be reduced using the Multi-Objectives Model and Genetic Algorithm. By coordinating the duties at each workstation, the mixed model results help to decrease queuing. Additionally, balancing the transfer of work to the stations is necessary to arrive at the best option.
Methodology:

We will be using the number of Assembly Line Balancing with the duration and the due date for each station.
Data collection and Analysis:
Arbitrary data will be used to find balancing the transfer of work to the stations necessary to arrive.
Expected Outcomes:
Thus, we have calculated the duration and due date of each station, we will be minimizing the delay by using the best decrease queuing sequence.