A genetic algorithm-based approach for flexible job shop rescheduling problem with machine failure interference

• Autorzy: Liang Zhongyuan , Zhong Peisi , Zhang Chao , Yang Wenlei , Xiong Wei , Yang Shihao , Meng Jing

Identyfikatory

DOI

10.17531/ein/171784

• Języki publikacji: EN

Abstrakty

EN

Rescheduling is the guarantee to maintain the reliable operation of production system process. In production system, the original scheduling scheme cannot be carried out when machine breaks down. It is necessary to transfer the production tasks in the failure cycle and replan the production path to ensure that the production tasks are completed on time and maintain the stability of production system. To address this issue, in this paper, we studied the event-driven rescheduling policy in dynamic environment, and established the usage rules of right-shift rescheduling and complete rescheduling based on the type of interference events. And then, we proposed the rescheduling decision method based on genetic algorithm for solving flexible job shop scheduling problem with machine fault interference. In addition, we extended the "mk" series of instances by introducing the machine fault interference information. The solution data show that the complete rescheduling method can respond effectively to the rescheduling of flexible job shop scheduling problem with machine failure interference.

Słowa kluczowe

EN

genetic algorithm; rescheduling; machine failure; flexible job shop scheduling

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 4
• Strony: art. no. 171784
• Opis fizyczny: Bibliogr. 35 poz., rys., tab., wykr.

Twórcy

autor

Liang Zhongyuan

• Advanced Manufacturing Technology Center, Shandong University of Science and Technology, China

• https://orcid.org/0000-0002-8372-3815

autor

Zhong Peisi

• Advanced Manufacturing Technology Center, Shandong University of Science and Technology, China

• https://orcid.org/0000-0003-3162-8098

autor

Zhang Chao

• Advanced Manufacturing Technology Center, Shandong University of Science and Technology, China

• https://orcid.org/0000-0002-6770-4294

autor

Yang Wenlei

• Qingdao Innovation and Development Base, Harbin Engineering University, China

autor

Xiong Wei

• China Railway Jinan Bureau Group Co., Ltd, China

autor

Yang Shihao

• Advanced Manufacturing Technology Center, Shandong University of Science and Technology, China

autor

Meng Jing

• Qingdao Haier Air Conditioner Co., Ltd, China

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