Solving Type-I unpaced synchronous mixed-model two-sided assembly line balancing problem using a genetic algorithm

This research aims to propose a genetic algorithm for the Type-I unpaced synchronous mixed-model two-sided assembly line balancing problem. A major challenge in addressing this problem is that the assembly line has the characteristic of variable output, requiring the solution approach to generate feasible solutions where the process time of certain workstations may exceed the given cycle time, while the average output time of the assembly line must not exceed this cycle time. To address this, the proposed algorithm incorporates a mechanism referred to as pre-allocation and formal allocation. It first assigns tasks to the currently active workstation, then evaluates whether the task assignment results meet the given cycle time, and adjusts them accordingly. This paper first models and analyzes the problem, then introduces the proposed genetic algorithm and illustrates its key steps through an example. Finally, experimental research is performed to demonstrate the effectiveness of the algorithm. The experimental results show that the proposed algorithm can construct solutions that match the characteristics of the problem.