Hybrid flow-shop scheduling problem considering joint of machine and AGV with renewable energy

被引：0

作者：

Zhu, Guangyu ^{[1
,2
]}

Jia, Weihong ^{[1
]}

Li, Debiao ^{[3
]}

机构：

[1] School of Advanced Manufacturing, Fuzhou University, Quanzhou

[2] School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou

[3] School of Economics and Management, Fuzhou University, Fuzhou

来源：

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2025年 / 51卷 / 02期

关键词：

A* algorithm; hybrid flow-shop scheduling; joint scheduling; multi-objective optimization; renewable energy;

D O I：

10.13700/j.bh.1001-5965.2023.0021

中图分类号：

学科分类号：

摘要：

The manufacturing industry in China is undergoing a digital and green low-carbon transformation. To achieve energy saving and emission reduction and improve the equipment utilization rate, a mathematical model of the hybrid flow-shop scheduling problem considering the joint of machine and automated guided vehicle (AGV) with renewable energy (HFSP-MA-RE) was established.To resolve this model, a joint scheduling strategy and an energy distribution strategy of machines and AGVs based on advance scheduling were proposed. In the case of AGV path optimization and charging constraints, four objectives of the maximum completion time, carbon emissions, total energy consumption, and AGV utilization rate were optimized.The multi-objective optimal foraging algorithm based on a positive projection gray target (PPGT_OFA) was constructed to resolve this problem. Through twenty-four test cases and one engineering application, the proposed algorithm and five multi-objective optimization algorithms were tested to verify the effectiveness of the HFSP-MA-RE model and PPGT_OFA in solving this multi-objective optimization problem. © 2025 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

引用

页码：368 / 379

页数：11

共 28 条

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