Enterprise-wide optimization: integrating planning, scheduling and control problems using feasibility analysis and surrogate models
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Scholz Dias, Lisia Marina.
Enterprise-wide optimization: integrating planning, scheduling and control problems using feasibility analysis and surrogate models. Retrieved from
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TitleEnterprise-wide optimization: integrating planning, scheduling and control problems using feasibility analysis and surrogate models
Date Created2019
Other Date2019-10 (degree)
Extent1 online resource (xi, 188 pages) : illustrations
DescriptionThe US Industrial manufacturers face numerous challenges such as increasing complexity of production processes, fluctuating customer demands and expansion of supply chains. Output is expected to increase only 3.5% in 2019, according to the International Monetary Fund. The global expansion has weakened, foreign trade is at historically low levels, and nationalist governments around the world are threatening to further undermine the free flow of goods, creating more uncertainty and constraints upon manufacturing growth. In such a slow-growth environment, productivity gains are essential and there is an opportunity to profit from innovative strategies. In the field of operations research and process systems engineering, the main strategy to combat the emerging challenges and improve the efficiency of process industry is the pursue of optimal operating conditions through an enterprise-wide optimization (EWO).
EWO involves optimizing the operations of supply, manufacturing and distributions activities of a company. A major focus in EWO is the optimal operation of manufacturing facilities, which involves the decision-making processes of planning, scheduling and real-time operational control. Traditionally, these decision-making problems are addressed individually and in a hierarchical manner, solved in a sequential way. An upper level problem is often solved with few or none information from lower levels. Its result is then transmitted to the lower levels, which must be optimized given the conditions already set by upper level problems. Consequently, sequential approaches may result in sub-optimal and infeasible solutions that can be avoided by an appropriate integration of different decision layers.
The objective of this work is to provide tools and the technology to establish optimal operating conditions by modernizing and integrating the decision-making process within a company. The integration is achieved by using simulation-based optimization techniques, surrogate modelling and feasibility analysis to transmit the information from lower levels to upper levels of the decision-making hierarchy. The problem of integrating scheduling and control is first addressed, followed by the problem of integrating planning and scheduling problems. By coupling the fundamentals of the developed integration strategies, enterprise wide optimization is achieved. The problem of planning, scheduling and control of a complex industrial-sized problem is then solved to demonstrate the adaptability, viability and performance of the proposed framework.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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