A Heuristic-Mixed Genetic Algorithm for Type II Assembly Line Balancing with Multiple Workers in Workstations

Abstract

A type II line balancing problem with multiple workers in workstations (mALBP-II) is considered given a total number of workers, group workers, and tasks into workstations so as to minimize cycle time. Different from the manufacturing environment where the traditional assembly line balancing problem (ALBP) rises, manual or semimanual manufacturing enjoys much higher flexibility allowing multiple workers to perform the same set of tasks on workpieces in the same workstation in parallel. The freedom of specifying the number of workers in workstations makes the classic NP-hard ALBP even harder to solve. A heuristic-mixed genetic algorithm (hGA) is therefore proposed to solve the problem. The algorithm minimizes cycle time as its first objective and balances workload among workstations as its second objective. A maximum-utilization heuristic and a bisection search are integrated into the decoding process of hGA so that the optimization of task assignment and worker allocation is accomplished simultaneously. Numerical results and a real-life application demonstrate the efficiency and effectiveness of hGA.