Flexible Assembly Job Shop Scheduling Considering Assembly Sequence Variation Under Dual-Resource Constraints Using Discrete Barnacles Mating Optimizer Algorithm

Abstract

To realize concurrent part processing and assembly process effectively in certain production scenarios, a method of flexible assembly job shop scheduling considering assembly sequence variation under dual-resource constraints (FAJSS-ASVDRC) including machine and worker is proposed. By analyzing the problems in FAJSS-ASVDRC, an integrated scheduling mathematical model that considers the interactive effects between part processing sequence and assembly sequence under dual-resource constraints is established, aiming to minimize the total production completion time, the total inventory time and the total labor cost in the production process. Based on above, a discrete barnacles mating optimizer (DBMO) algorithm is proposed to solve the FAJSS-ASVDRC problem. In DBMO, a three-layer hybrid chromosome encoding structure is designed, two reproduction methods are proposed by mimicking the reproduction way of barnacles to generate offspring chromosomes, and a mutation operator based on the assembly operations is designed to ensure the diversity of the solutions. In the case study, the Taguchi method is used to obtain the best combination of parameters for the DBMO algorithm. Then, the proposed FAJSS-ASVDRC method is verified to be able to improve the production efficiency more effectively compared to traditional methods, the three objective function values are reduced by 33.7%, 76.8% and 9.8%, respectively. Additionally, the effectiveness of DBMO algorithm is verified to outperform other algorithms in more than 75% cases with different scale in solving the FAJSS-ASVDRC problem.

Keywords

• Flexible assembly job shop scheduling
• assembly sequence variation
• assembly sequence planning
• dual-resource constraints
• barnacles mating optimizer algorithm