Lot streaming Permutation Flow shop with energy awareness

被引:4
作者
D'Amico, F. [1 ]
Rossit, D. A. [1 ,2 ]
Frutos, M. [1 ,3 ]
机构
[1] Univ Nacl Sur, Dept Ingn, Bahia Blanca, Buenos Aires, Argentina
[2] UNS, CONICET, INMABB, Bahia Blanca, Buenos Aires, Argentina
[3] UNS, CONICET, IIESS, Bahia Blanca, Buenos Aires, Argentina
来源
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND MANAGEMENT | 2021年 / 12卷 / 01期
关键词
Scheduling; Flow shop; Energy consumption; Sustainability; POWER-CONSUMPTION;
D O I
10.24867/IJIEM-2021-1-274
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this work, the flow shop scheduling problem with energy awareness is approached with lot-streaming strategies. Energy consumption is modeled within the objective function, together with the makespan, by means of a normalized and weighted sum. Thus, reducing energy consumption guides the optimization process. For lot streaming approaches mathematical models are provided and assessed. The results showed that lot-streaming is an efficient strategy to address this problem, allowing to improve both makespan and total energy consumption compared to the problem without lot-streaming. In turn, the selection of processing speeds for each sublot was incorporated, which improved the strategy yielding the best quality solutions.
引用
收藏
页码:25 / 36
页数:12
相关论文
共 23 条
  • [1] The Non-Permutation Flow-Shop scheduling problem: A literature review
    Alejandro Rossit, Daniel
    Tohme, Fernando
    Frutos, Mariano
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2018, 77 : 143 - 153
  • [2] Bach T. Marceda, 2018, INT J IND ENG MANAGE, V9, P31
  • [3] Briem A.-K., 2019, INT J IND ENG MANAGE, P171, DOI [10.24867/IJIEM-2019-2-237, DOI 10.24867/IJIEM-2019-2-237]
  • [4] Energy-aware scheduling for improving manufacturing process sustainability: A mathematical model for flexible flow shops
    Bruzzone, A. A. G.
    Anghinolfi, D.
    Paolucci, M.
    Tonelli, F.
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2012, 61 (01) : 459 - 462
  • [5] Bynum Michael L., 2021, Pyomo-Optimization Modeling in Python, V67
  • [6] Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm
    Dai, Min
    Tang, Dunbing
    Giret, Adriana
    Salido, Miguel A.
    Li, W. D.
    [J]. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2013, 29 (05) : 418 - 429
  • [7] Flow shop scheduling with peak power consumption constraints
    Fang, Kan
    Uhan, Nelson A.
    Zhao, Fu
    Sutherland, John W.
    [J]. ANNALS OF OPERATIONS RESEARCH, 2013, 206 (01) : 115 - 145
  • [8] A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction
    Fang, Kan
    Uhan, Nelson
    Zhao, Fu
    Sutherland, John W.
    [J]. JOURNAL OF MANUFACTURING SYSTEMS, 2011, 30 (04) : 234 - 240
  • [9] Lot Streaming Flow Shop with a Heterogeneous Machine
    Ferraro, Augusto
    Rossit, Daniel
    Toncovich, Adrian
    Frutos, Mariano
    [J]. ENGINEERING MANAGEMENT JOURNAL, 2019, 31 (02) : 113 - 126
  • [10] Evolutionary Multiobjective Blocking Lot-Streaming Flow Shop Scheduling With Machine Breakdowns
    Han, Yuyan
    Gong, Dunwei
    Jin, Yaochu
    Pan, Quanke
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2019, 49 (01) : 184 - 197