Assembly line balancing with product and operator oriented sequence dependent task times using tabu search algorithm

The problem is formulated as a mixed-integer nonlinear programming model, with the objective of minimizing sequence-dependent setups while meeting specified cycle time and station count constraints. A tabu search algorithm is proposed to solve the resulting mathematical model, and its performance is assessed through numerical experiments. The developed numerical examples demonstrate significant improvements in setup time reduction. Notably, a substantial enhancement—a 91% reduction in setup time—is observed in moderate-sized problems ( n = 50) characterized by high precedence density (OS = 0.6). Subsequently, the developed tabu search algorithm is applied to address the assembly line balancing problem encountered by a leading air conditioner manufacturer. Numerical experiments indicate that the algorithm yields an approximate 10% reduction in both product and operator-oriented setups, showing its effectiveness in enhancing assembly line efficiency. Future research could explore how the developed approach to be applied in various industrial settings including multi-model or mixed-model assembly lines.