Theory and Solution Methods for Chemical Production Scheduling
Theory and Solution Methods for Chemical Production Scheduling
批准号:
1066206
负责人:
Christos Maravelias
金额:
$31.44万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-04-01 至 2014-03-31
中文摘要
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英文摘要
PI: Maravelias, Christos Institution: University of WisconsinProposal Number: 1066206Title: Theory and Solution Methods for Chemical Production SchedulingTo remain competitive in todays global environment, US chemical companies have moved towards product customization and diversification, which in turn have resulted in a large number of low-volume, high-value products. Furthermore, in an effort to achieve higher utilization of resources, chemical manufacturers have started to employ multiproduct/multipurpose facilities. In addition to higher resource utilization, the flexibility of these facilities allows for lower inventory costs and better responsiveness to demand fluctuations. However, these advantages can be achieved only if effective optimization-based production scheduling methodologies, which could uncork the hidden potential of multiproduct manufacturing, are developed. The two major bottlenecks in the development and adoption of such methods appear to be: a) the lack of an unambiguous problem statement, which prohibits the development of a unified information technology framework; and b) the computational performance of existing optimization-based methods. The goal of this research is the development of new theory and solution methods that will address the second challenge.Intellectual Merit The intellectual merit is in the analysis of existing frameworks, the development of the underlying optimization theory, and the formulation of advanced solution strategies for chemical production scheduling. This project will focus on the following five areas:a) Method classification formulate a systematic classification of general scheduling approaches and modeling techniques.b) Computational study perform an extensive computational study of various approaches using more than 5,000 problem instances. c) Theory development develop mathematical properties regarding the tightness of scheduling mixed-integer programming formulations.d) Novel Modeling Methods use the inherent structure of scheduling models and our theoretical results to explore ways of strengthening these formulations.e) Solution algorithms based on the computational and theoretical results, study new decomposition schemes and explore new search methods and design algorithms that harness the new capabilities offered by parallel computing and cyberinfrastructure.Broader ImpactThis research will advance the state of the art in the use of optimization methodologies in process operations, thereby opening new avenues of research in process systems engineering (PSE). Through the involvement of the graduate student working on this project, the results of will be used to develop educational material for a graduate level course the PI teaches. Furthermore, this material will be evaluated for effectiveness and disseminated through the Engineering Pathway and the National Science Digital Library. Both the codes and the library of problems developed during this project will be made publicly available so that others in the field can replicate (or improve upon) the results. This project will also offer the PI an opportunity to further develop his undergraduate research program. Specifically, undergraduate students will use some of the cyber-infrastructure tools developed in this effort to carry out computational studies.Potentially Transformative ResearchThis research is a major departure from previous work in this area in that it will be based upon a theoretical study of the structure of mixed-integer programming formulations and the derivation of mathematical properties on their polyhedral properties. This is a subject that has received practically no attention to this point in the PSE literature. Therefore, if successful, the research will lay the foundations of a new, theoretically rigorous approach to production scheduling, which could lead to significant advances in solving broad families of operational problems.
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批准号:2026980
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项目类别:Standard Grant
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依托单位:
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