Workload-based order acceptance in seru production system

被引:5
|
作者
Wang, Yulong [1 ]
Zhang, Zhe [1 ]
Yin, Yong [2 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing, Peoples R China
[2] Doshisha Univ, Grad Sch Business, Kamigyo Ku, Kyoto, Japan
基金
中国国家自然科学基金;
关键词
seru production system; seru loading; order acceptance; genetic algorithm;
D O I
10.1504/IJMR.2020.108197
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper focuses on the seru loading problem considering order acceptance. In practice, manufacturing company may receive a certain number of orders before the planning period, and each of them has the different processing time, setup time, revenue, tardiness penalty and due date. Due to the limitation of production capacity, the manufacturing company need to make order acceptance and loading decision to maximise profits. According to the parallel structure of seru production system and the characteristics of proposed model, the genetic algorithm with matrix crossover (MCGA) is designed. Finally, two numerical examples are applied to show the practicability and effectiveness of proposed model and algorithm. [Submitted 19 June 2018; Accepted 7 November 2018]
引用
收藏
页码:234 / 251
页数:18
相关论文
共 50 条
  • [31] Workload-based dynamic voltage scaling with the QoS for streaming video
    Wang, Hong Moon
    Choi, Hyun Suk
    Kim, Jong Tae
    DELTA 2008: FOURTH IEEE INTERNATIONAL SYMPOSIUM ON ELECTRONIC DESIGN, TEST AND APPLICATIONS, PROCEEDINGS, 2008, : 236 - 239
  • [32] A workload-based nonlinear approach for predicting available computing resources
    JIA Yunfei
    ZHOU Zhiquan
    WU Renbiao
    JournalofSystemsEngineeringandElectronics, 2020, 31 (01) : 224 - 230
  • [33] Workload-based randomization byzantine fault tolerance consensus protocol
    Huang, Baohua
    Peng, Li
    Zhao, Weihong
    Chen, Ningjiang
    HIGH-CONFIDENCE COMPUTING, 2022, 2 (03):
  • [34] A workload-based nonlinear approach for predicting available computing resources
    Jia Yunfei
    Zhou Zhiquan
    Wu Renbiao
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2020, 31 (01) : 224 - 230
  • [35] A Workload-Based Dynamic Adaptive Data Replica Placement Method
    Guo, Wei
    Wang, Xinjun
    Dong, Yongquan
    2014 11TH WEB INFORMATION SYSTEM AND APPLICATION CONFERENCE (WISA), 2014, : 184 - 187
  • [36] A comparative workload-based methodology for performance evaluation of parallel computers
    Onbasioglu, E
    Paker, Y
    FUTURE GENERATION COMPUTER SYSTEMS, 1997, 12 (06) : 521 - 545
  • [37] An efficient workload-based data layout scheme for multidimensional data
    Zaman, KA
    Padmanabhan, S
    DATA & KNOWLEDGE ENGINEERING, 2001, 39 (03) : 271 - 291
  • [38] Dynamic workload-based partitioning algorithms for continuously growing databases
    Liroz-Gistau, Miguel
    Akbarinia, Reza
    Pacitti, Esther
    Porto, Fabio
    Valduriez, Patrick
    1600, Springer Verlag (8320 LNCS): : 105 - 128
  • [39] Determining diagnostic radiographer staffing requirements: A workload-based approach
    Bam, L.
    Cloete, C.
    de Kock, I. H.
    RADIOGRAPHY, 2022, 28 (02) : 276 - 282
  • [40] Predicting Failure Probability in Industry 4.0 Production Systems: A Workload-Based Prognostic Model for Maintenance Planning
    Converso, Giuseppe
    Gallo, Mose
    Murino, Teresa
    Vespoli, Silvestro
    APPLIED SCIENCES-BASEL, 2023, 13 (03):