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Advances in Optimization-based Methods for Planning and Scheduling of Supply Chains in Process Systems

Advances in Optimization-based Methods for Planning and Scheduling of Supply Chains in Process Systems The development of optimization models for planning and scheduling of chemical processes has received significant attention over the last ten years in the area of process systems engineering. Major reasons are the large potential savings that can be achieved by improving the logistics of manufacturing in large-scale continuous proc-esses, as well as in batch manufacturing facilities (e.g. lower inventories, lower transi-tion costs, reduction in production shortfalls). Furthermore, the interest in planning and scheduling has increased with industry’s goal of improving the management and dynamics of their supply chains. In this talk we first provide an overview of planning and scheduling in the process industry, emphasizing both the modeling and computational challenges. We discuss the great variety of considerations that make it extremely challenging to develop general purpose models, as well as solution methods that computationally do not scale exponentially with the size of the problem. We then review mathematical program-ming methods, including the traditional mixed- integer programming techniques, and the recent logic-based optimization methods such as generalized disjunctive pro-gramming and constraint programming. We also examine how to integrate these techniques through Lagrangian decomposition techniques. The specific applications that we will discuss, which have been a result of collaborations with industry, include scheduling of batch plants, multisite production planning of continuous processes, dynamics and optimization of supply chains, long-range planning of off-shore oilfield infrastructures, scheduling of tests for new pharmaceutical and agrochemical products and their integration with manufacturing planning. As will be shown in each of these cases solution techniques have been developed that have led to success stories in real world problems.
Type of Seminar:
Public Seminar
Prof. Ignacio Grossmann
Automatic Lab - D-ITET - 8092 Zürich and Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, 15213, U.S.A
Apr 05, 2004   16:15

University of Zürich, Zentrum, room: KO2-F-172
Contact Person:

Prof. H. Garbers
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Biographical Sketch:
Ignacio E. Grossmann is the Rudolph R. and Florence Dean University Professor of Chemical Engineering, and former Department Head at Carnegie Mellon University. He obtained his B.S. degree in Chemical Engineering at the Universidad Iberoamericana, Mexico City, in 1974, and his M.S. and Ph.D. in Chemical Engineering at Imperial College in 1975 and 1977, respectively. After working as an R&D engineer at the Instituto Mexicano del Petróleo in 1978, he joined Carnegie Mellon in 1979. He was Director of the Synthesis Laboratory from the Engineering Design Research Center in 1988-93. He is currently member of the "Center for Advanced Process Decision-making" which comprises a total of 15 chemical and petroleum companies. Ignacio Grossmann is a member of the National Academy of Engineering, Mexican Academy of Engineering, and associate editor of AIChE Journal and member of editorial board of Computers and Chemical Engineering, Journal of Global Optimization, Optimization and Engineering, and Latin American Applied Research. Major awards include the 1984 Presidential Young Investigator Award, the 1994 Computing in Chemical Engineering Award of the CAST Division of AIChE, the 1997 William H. Walker Award of AIChE, in 2002 Honorary Doctor in Technology from Åbo Akademi in Finland, Fellow of INFORMS and Top 15 Most Cited Author in Computer Science by ISI, and the recipient of the 2003 Computer Society Prize of INFORMS. He was also recipient of the Best Technical Paper in 1988, 1996, 1998 and 2000 of Computers and Chemical Engineering. The research interests of Ignacio Grossmann are in the areas of process synthesis, energy integration, planning and scheduling of batch and continuous processes, supply chain optimization, optimization under uncertainty, and mixed-integer and logic-based optimization. He has authored more than 200 papers, several monographs on design cases studies, and the textbook "Systematic Methods of Chemical Process Design." Professor Grossmann has graduated 34 Ph.D. and 3 M.S. students.