A polynomial-time scheduling approach to minimise idle energy consumption: An application to an industrial furnace

被引:4
作者
Benedikt, Ondrej [1 ,2 ]
Alikoc, Baran [1 ]
Sucha, Premysl [1 ]
Celikovsky, Sergej [3 ]
Hanzalek, Zdenek [1 ]
机构
[1] Czech Tech Univ, Czech Inst Informat Robot & Cybernet, Prague, Czech Republic
[2] Czech Tech Univ, Fac Elect Engn, Prague, Czech Republic
[3] Czech Acad Sci, Inst Informat Theory & Automat, Prague, Czech Republic
关键词
Scheduling; Energy optimisation; Operational research; Optimal control; Electric furnaces; ALGORITHM;
D O I
10.1016/j.cor.2020.105167
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This article presents a novel scheduling approach to minimise the energy consumption of a machine dur -ing its idle periods. In the scheduling domain, it is common to model the behaviour of the machine by defining a small set of machine modes, e.g. "on", "off" and "stand-by". Then the transitions between the modes are represented by a static transition graph. In this paper, we argue that this type of model might be too restrictive for some types of machines (e.g. the furnaces). For such machines, we propose to employ the complete time-domain dynamics and integrate it into an idle energy function. This way, the scheduling algorithm can exploit the full knowledge about the machine dynamics with minimised energy consumption encapsulated in this function. In this paper, we study a scheduling problem, where the tasks characterised by release times and deadlines are scheduled in the given order such that the idle energy consumption of the machine is minimised. We show that this problem can be solved in polyno-mial time whenever the idle energy function is concave. To highlight the practical applicability, we analyse a heat-intensive system employing a steel-hardening furnace. We derive an energy optimal control law, and the corresponding idle energy function, for the bilinear system model approximating the dynamics of the furnace (and possibly other heat-intensive systems). Further, we prove that the idle energy function is, indeed, concave in this case. Therefore, the proposed scheduling algorithm can be used. Numerical experiments show that by using our approach, combining both the optimal control and optimal scheduling, higher energy savings can be achieved, compared to the state-of-the-art schedul-ing approaches. (c) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:15
相关论文
共 32 条
  • [1] Energy cost minimization for unrelated parallel machine scheduling under real time and demand charge pricing
    Abikarram, Jose Batista
    McConky, Katie
    Proano, Ruben
    [J]. JOURNAL OF CLEANER PRODUCTION, 2019, 208 : 232 - 242
  • [2] Complexity analysis of energy-efficient single machine scheduling problems
    Aghelinejad, MohammadMohsen
    Ouazene, Yassine
    Yalaoui, Alice
    [J]. OPERATIONS RESEARCH PERSPECTIVES, 2019, 6
  • [3] Production scheduling optimisation with machine state and time-dependent energy costs
    Aghelinejad, MohammadMohsen
    Ouazene, Yassine
    Yalaoui, Alice
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2018, 56 (16) : 5558 - 5575
  • [4] Angel E., 2012, LATIN 2012 THEORETIC, pS
  • [5] [Anonymous], 2009, PRINCIPLES SEQUENCIN, DOI DOI 10.1002/9780470451793
  • [6] Baptiste P, 2007, LECT NOTES COMPUT SC, V4698, P136
  • [7] Optimizing energy consumption of robotic cells by a Branch & Bound algorithm
    Bukata, Libor
    Sucha, Premysl
    Hanzalek, Zdenek
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2019, 102 : 52 - 66
  • [8] Energy Optimization of Robotic Cells
    Bukata, Libor
    Sucha, Premysl
    Hanzalek, Zdenek
    Burget, Pavel
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (01) : 92 - 102
  • [9] Energy-conscious unrelated parallel machine scheduling under time-of-use electricity tariffs
    Che, Ada
    Zhang, Shibohua
    Wu, Xueqi
    [J]. JOURNAL OF CLEANER PRODUCTION, 2017, 156 : 688 - 697
  • [10] Energy-efficient bi-objective single-machine scheduling with power-down mechanism
    Che, Ada
    Wu, Xueqi
    Peng, Jing
    Yan, Pengyu
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2017, 85 : 172 - 183