Energy-Saving Workshop Scheduling Method Based on Synchronous Optimization of Equipment Tasks and Interval States

Hong Cheng (), Shuo Zhu, Zhigang Jiang, Hua Zhang and Wei Yan
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Hong Cheng: Wuhan University of Science and Technology, Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering
Shuo Zhu: Wuhan University of Science and Technology, Key Laboratory of Metallurgical Machine and Control Technology, Ministry of Education
Zhigang Jiang: Wuhan University of Science and Technology, Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering
Hua Zhang: Wuhan University of Science and Technology, Academy of Green Manufacturing Engineering
Wei Yan: Wuhan University of Science and Technology, Key Laboratory of Metallurgical Machine and Control Technology, Ministry of Education

A chapter in Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024), 2025, pp 140-146 from Springer

Abstract: Abstract Task allocation and the control of equipment interval states significantly impact energy consumption in workshops, making them crucial for achieving overall energy savings. However, current asynchronous optimization methods face limitations due to the strong constraints imposed by task allocation on equipment state control. This study proposes a scheduling method that synchronously optimizes equipment tasks and interval state control. Firstly, the influence of equipment states (idle, standby, stop) on energy consumption is analyzed within different interval times resulting from task allocation. By examining the relationship between changes in equipment interval states and energy fluctuations, three energy-saving scheduling strategies that integrate state control are developed. Secondly, relevant variables related to interval states and energy consumption are extracted to establish an energy-saving scheduling model for synchronous optimization. An improved multi-objective whale optimization algorithm (MOWOA) is then designed, incorporating scheduling adjustments and energy-saving strategies into chromosome encoding to address the energy-saving scheduling model. Finally, a case study involving the machining of engine parts demonstrates the effectiveness of the proposed method. The results indicate that the generated Gantt chart accurately reflects both equipment task allocation and interval state control outcomes.

Keywords: Workshop Energy-saving Scheduling; Equipment Interval States Control; Synchronous Optimization; Improved WOMOA (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-676-5_16

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