Systematic Mathematical Strategies for Stochastic Modeling and Uncertainty in Production Planning and Scheduling

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ABSTRACTPI: Marianthi Ierapetritou Institution: Rutgers UniversityProposal Number: 0625515Title: Systematic Mathematical Strategies for Stochastic Modeling and Uncertainty in Production Planning and SchedulingProject SummaryOptimization of process operations for a single production facility involves a large number of interdependent factors that need to be considered involving economic optimality, demand satisfaction, capacity limitations, production recipe, sequence dependent tasks, etc. Existing models attempt to develop a compromise between a realistic description of the problem, and available capabilities in terms of solution procedures. This project targets methodologies to deal with uncertainty in production planning. The integrated framework that is planned targets a key issue in the area of optimizing production systems, which is the problem of uncertainty. The main outcome is to provide alternative solutions to the decision maker that exhibit different characteristics in the face of uncertainty, namely expected profitability, flexibility, and robustness. To achieve this target, the following ideas will be investigated depending on the level of information available about uncertainty: Sensitivity analysis and parametric programming in the uncertainty space. New ideas will be investigated that will enable the efficient generation of parametric solutions for the case where there is not sufficient information to characterize uncertainty. Multi-objective optimization considering risk and profitability in the early decision stages that will result in solutions that balance appropriately the different objectives. This approach will be employed in the cases where there is available information to describe the uncertain parameters. The ultimate goal is to optimize the production planning operations in large-scale, single-facility production plants considering the issues of uncertainty. Realistic case studies and actual examples from petrochemical companies, fast moving consumer goods manufacturing and chemical companies will be utilized to test and verify the results of the proposed analysis tools. Broad Impact The impact of the work goes beyond specific industrial sector operations since the general ideas and findings can be applied to many types of production facilities. The dissemination of the results through the development of a web-based environment will enable better interactions with industry. Among the targets of this project is the integration of the basic concepts of process operations, results and case studies within the chemical engineering curriculum. A restructured design course and a newly introduced interdisciplinary systems engineering course will be used as integration tools.