Optimization of Just-In-Time Part Supply Scheduling in Assembly Job Shop

摘要

Taking the actual assembly job shop as an example, this paper comprehensively considers the resource constraints of the assembly job shop, the capacity of distribution vehicle and the capacity constraints of the station temporary storage area. A mathematical model was constructed with the optimization goal of minimizing the inventory of the temporary storage area and the total transportation energy consumption without allowing the shortage of parts. Based on the idea of chaotic mapping and reverse learning, the food source coding and initialization were redesigned, and a modified discrete artificial bee colony algorithm was constructed to make joint decision on part supply time and delivery quantity. Finally, simulation analysis was performed to verify the feasibility and effectiveness of the algorithm and model.