On deterministic online scheduling: Major considerations, paradoxes and remedies

被引:53
作者
Gupta, Dhruv [1 ]
Maravelias, Christos T. [1 ]
机构
[1] Univ Wisconsin, Dept Chem & Biol Engn, 1415 Engn Dr, Madison, WI 53706 USA
基金
美国国家科学基金会;
关键词
Chemical production scheduling; Rescheduling; Mixed-integer programming; Closed-loop solution; SUBSTANTIAL DOWNSTREAM BENEFITS; MULTIMILLION-DOLLAR BENEFITS; ROBUST OPTIMIZATION APPROACH; MULTIPRODUCT BATCH PLANTS; CRUDE-OIL BLENDSHOP; MIP MODELS; INVENTORY MANAGEMENT; GENERAL ALGORITHM; UNCERTAINTY; FRAMEWORK;
D O I
10.1016/j.compchemeng.2016.08.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Despite research in the area, the relationship between the (open-loop) optimization problem and the quality of the (closed-loop) implemented schedule is poorly understood. Accordingly, we first show that open-loop and closed-loop scheduling are two different problems, even in the deterministic case. Thereafter, we investigate attributes of the open-loop problem and the rescheduling algorithm that affect closed-loop schedule quality. We find that it is important to reschedule periodically even when there are no "trigger" events. We show that solving the open-loop problem suboptimally does not lead to poor closed-loop solutions; instead, suboptimal solutions are corrected through feedback. We also observe that there exist thresholds for rescheduling frequency and moving horizon length, operating outside of which leads to substantial performance deterioration. Fourth, we show that the design attributes work in conjunction, hence, studying them simultaneously is important. Finally, we explore objective function modifications and constraint addition as methods to improve performance. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:312 / 330
页数:19
相关论文
共 62 条
[1]  
[Anonymous], 1998, Integer programming
[2]  
[Anonymous], 2015, HTCONDOR 8 5 0
[3]   Approximation to multistage stochastic optimization in multiperiod batch plant scheduling under demand uncertainty [J].
Balasubramanian, J ;
Grossmann, IE .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2004, 43 (14) :3695-3713
[4]   Scheduling optimization under uncertainty - an alternative approach [J].
Balasubramanian, J ;
Grossmann, IE .
COMPUTERS & CHEMICAL ENGINEERING, 2003, 27 (04) :469-490
[5]   Using detailed scheduling to obtain realistic operating policies for a batch processing facility [J].
Bassett, MH ;
Pekny, JF ;
Reklaitis, GV .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 1997, 36 (05) :1717-1726
[6]   Decomposition techniques for the solution of large-scale scheduling problems [J].
Bassett, MH ;
Pekny, JF ;
Reklaitis, GV .
AICHE JOURNAL, 1996, 42 (12) :3373-3387
[7]   Addressing robustness in scheduling batch processes with uncertain operation times [J].
Bonfill, A ;
Espuña, A ;
Puigjaner, L .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2005, 44 (05) :1524-1534
[8]   Risk management in the scheduling of batch plants under uncertain market demand [J].
Bonfill, A ;
Bagajewicz, M ;
Espuña, A ;
Puigjaner, L .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2004, 43 (03) :741-750
[9]   MINIMIZING THE EFFECTS OF BATCH PROCESS VARIABILITY USING ONLINE SCHEDULE MODIFICATION [J].
COTT, BJ ;
MACCHIETTO, S .
COMPUTERS & CHEMICAL ENGINEERING, 1989, 13 (1-2) :105-113
[10]   Medium-term planning of a multiproduct batch plant under evolving multi-period multi-uncertainty by means of a moving horizon strategy [J].
Cui, Jian ;
Engell, Sebastian .
COMPUTERS & CHEMICAL ENGINEERING, 2010, 34 (05) :598-619