Integration of Operational Planning and Medium-Term Scheduling for Large-Scale Industrial Batch Plants under Demand and Processing Time Uncertainty

被引:24
|
作者
Verderame, Peter M. [1 ]
Floudas, Christodoulos A. [1 ]
机构
[1] Princeton Univ, Dept Chem Engn, Princeton, NJ 08544 USA
基金
美国国家科学基金会;
关键词
ROBUST OPTIMIZATION APPROACH; SEMICONTINUOUS PLANTS; FORMULATION; SYSTEMS; DESIGN;
D O I
10.1021/ie901973e
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Operational planning, medium-term scheduling, and short-term scheduling are closely related activities. Despite prior advances, the effective integration of planning and scheduling under demand and processing time uncertainty remains a challenging problem, especially for large-scale industrial processes. To address this issue, a novel framework for the integration of planning and scheduling under demand due date and amount uncertainty, as well as batch processing time uncertainty is proposed. Both the robust operational planning with production disaggregation model and the operational conditional value-at-risk planning with production disaggregation model have been successfully interfaced with an industrially validated medium-term scheduling model by means of a rolling horizon framework used in conjunction with a novel feedback loop. Demand uncertainty is taken into account at the planning level, processing time uncertainty is addressed within the selected scheduling model, and a novel feedback loop allows for the two-way interaction between the planning and scheduling levels. An industrial case study has been conducted for a large-scale multipurpose and multiproduct batch plant capable of producing hundreds of products over a time horizon of 3 months in order to demonstrate the viability of the proposed approach.
引用
收藏
页码:4948 / 4965
页数:18
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