A model-based rescheduling framework for managing abnormal supply chain events

被引:46
作者
Adhitya, Arief [1 ]
Srinivasan, Rajagopalan [1 ]
Karimi, I. A. [1 ]
机构
[1] Natl Univ Singapore, Lab Intelligent Applicat Chem Engn, Dept Chem & Biomol Engn, Singapore 117576, Singapore
关键词
risk management; optimization; reactive scheduling; uncertainty; crude oil;
D O I
10.1016/j.compchemeng.2006.07.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Enterprises today have realized the importance of supply chain management to achieve operational efficiency, cut costs, and maintain quality. Uncertainties in supply, demand, transportation, market conditions, and many other factors can interrupt supply chain operations, causing significant adverse effects. These uncertainties motivate the development of decision support systems for managing disruptions in the supply chain. In this paper, we propose a model-based framework for rescheduling operations in the face of supply chain disruptions. A causal model, called the composite-operations graph, captures the cause-and-effect among all the variables in supply chain operation. Its subgraph, called scheduled-operations graph, captures the causal relationships in a schedule and is used for identifying the consequences of a disruption. Rescheduling is done by searching a rectifications-graph, which captures all possible options to overcome the disruption effects, based on a user-specified utility function. In contrast to heuristic approaches, the main advantages of the proposed model-based rescheduling method are the completeness of solution search and flexibility of the utility function. The proposed framework is illustrated using a refinery supply chain example. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:496 / 518
页数:23
相关论文
共 31 条
[1]   Rescheduling job shops under random disruptions [J].
Abumaizar, RJ ;
Svestka, JA .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1997, 35 (07) :2065-2082
[2]  
ADHITYA A, 2006, MANAGING ABNORMAL EV
[3]   Match-up scheduling under a machine breakdown [J].
Akturk, MS ;
Gorgulu, E .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1999, 112 (01) :81-97
[4]   Executing production schedules in the face of uncertainties: A review and some future directions [J].
Aytug, H ;
Lawley, MA ;
McKay, K ;
Mohan, S ;
Uzsoy, R .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2005, 161 (01) :86-110
[5]   Combining knowledge-based systems and simulation to solve rescheduling problems [J].
Belz, R ;
Mertens, P .
DECISION SUPPORT SYSTEMS, 1996, 17 (02) :141-157
[6]  
BUSSMANN S, 2004, MULTIAGENTS SYSTEMS
[7]   How airlines and airports recover from schedule perturbations: A survey [J].
Filar, JA ;
Manyem, P ;
White, K .
ANNALS OF OPERATIONS RESEARCH, 2001, 108 (1-4) :315-333
[8]  
HENSELER H, 1994, ARTIF INTELL, P19
[9]  
Herroelen W, 2004, INT J PROD RES, V42, P1599, DOI [10.1080/00207540310001638055, 10.1080/00207543310001638055]
[10]  
JO GS, 2000, AI MAGAZINE WIN, P75