A new hybrid intelligent method for assembly line balancing

Abstract

A new hybrid intelligent method for solving assembly line balancing problems is proposed in this paper. The tabu search (TS) method and the genetic algorithm (GA) are combined to identify and provide solutions for assembly line balancing problems. The approach is named the TSGA-based method. With the proposed approach, the TS method can well address the number of tasks assigned for each workstation, whereas the GA can also assign the sequence of tasks for each workstation according to precedence constraints. In this paper, four single-model assembly line balancing problems from a survey of literature are tested against the proposed approach. From the simulation results compared with the conventional method, it was found that the proposed TSGA-based method is capable of producing solutions superior to the conventional method. It can be concluded that the TSGA-based method is an alternative potential algorithm to solve assembly line balancing problems. © 2007 IEEE.