Collaborative Scheduling Optimization Method for Multi-Stage Automobile Engine Hybrid Flow Shop
Year: 2024
Type: conference-paper
Abstract: The production of automobile engines needs to be completed through three workshops: casting, machining and assembly. As a serial production system, the stagnation of any link will affect the normal operation of downstream production, causing work-in-process inventory increase and production delay. Therefore, it is necessary to make a reasonable scheduling arrangement for the whole production system. To address this issue, considering the production features and multi-stage workshop collaboration relationships, a collaborative scheduling optimization method is proposed for a multi-stage hybrid flow shop of automobile engines. Firstly, the collaborative production relationship between workshops is analyzed. Taking the collaborative production cost and the maximum completion time as the optimization objectives, a collaborative scheduling optimization model of automobile engine multi-stage hybrid flow shop is established. Then, considering the discrete type of scheduling problem, the encoding/decoding strategies based on the random key strategies are studied to bridge the gaps between the continuous algorithm and the discrete problem. Subsequently, a distributed reference vector guided evolutionary algorithm is proposed to solve the model with high efficiency and reliability. Finally, taking the factual production of an automobile engine enterprise as a case for experiment and comparative analysis, the effectiveness and superiority of the proposed method are verified.
Authors: Hewang Zhai, Congbo Li, Wei Wu, Maokun Xiong, Miao Yang
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4406612025