Modeling and balancing of parallel U-shaped assembly line based on improved genetic algorithms

Abstract

Aiming at the improvement of the efficiency of the assembly line in the intelligent manufacturing field, a parallel U-shaped assembly line balancing problem (PUALBP) appears. In this paper, a mathematical model of the PUALBP-I is established, and an improved genetic algorithm (IGA) is innovatively designed based on the allocation strategy. Combined with 56 classic examples, the IGA is used to solve the mathematical models of SUAL and PUAL respectively, and the balance results and the balance effect evaluation indicators are obtained. The comparison with Parallel U-line Heuristic (PUH) shows that the results of PUAL are better than SUAL, and verifies that the IGA is effective. The results demonstrate that the IGA in calculating large-scale problems is superior to the small-scale problems, which provides a useful reference for solving PUALBP.