The new MILP mathematical model for optimization of complex assembly lines with the ABC-PSO method

The problem of balancing assembly lines is one of the optimization problems that have been studied by many researchers. However, after six decades of research and development, there is a profound gap between academic studies in this area and the practical applications of the assembly line balancing problem in the real industry environment. For this reason, this study aimed to balance the complex assembly lines in order to reduce the cost of manpower and reduce the number of workstations. To solve the problem from the dataset consisting of 7 workstations and 70 tasks and the time to solve 500 seconds and the time of performing each activity including 260 specific activities, two general approaches are used to determine the prerequisite relationships. Gams model software is resolved. Then the problem is solved once again with the modified honeycomb algorithm in MATLAB software and finally solved by the new hybrid honeycomb algorithm with PSO method and finally the obtained values of the objective function of both methods are combined. Have been compared and the results show that the hybrid honeycomb algorithm is optimized at the same early stages of optimization and its objective function value reaches its minimum value and also obtained the least amount of constraint violation and shows cost and cost reductions. Reduces workstations to 3.