Optimization of Line Balancing for Flexible Machining Lines Based on Multiobjective Genetic Algorithm

Abstract:

To solve line balancing problems for flexible machining line, a method was proposed, which can provide optimal stations configuration and operations assignment and sequence. After analyzing precedence constraint, clustering constraint and station constraint decided by machine capability, setups and workpiece orientation, a mathematical model was constructed, in which three objectives were considered simultaneously: number of machines, cycle time, line balancing rate. The multiobjective genetic algorithm (MOGA) was presented. A heuristic population generation and a heuristic decoder were designed. The Pareto ranking method and the sharing function method were employed to evaluate the individuals’ fitness, which guaranteed the dispersity and uniformity of the solutions. A case study for cylinder block machining line was carried out, and multiple optimal solutions were obtained by the MOGA. The computational results demonstrate the feasibility and effectiveness of the proposed algorithm.