Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Proth, J.M.Subject: search.filters.subject.clustering

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    Hierarchical Production Planning for Complex Manufacturing
    (1994) Mehra, Anshu; Minis, Ioannis; Proth, J.M.; ISR
    A hierarchical approach to production planning for complex manufacturing systems is presented. A single facility comprising of a number of work-centers that produce multiple part types is considered. The planning horizon includes a sequence of time periods, and the demand for all part types is assumed to be known. The production planning problem consists of minimizing the holding costs for all part types as well as the work-in- process, and the backlogging cost for the end items. We present a two- level hierarchy that is based on aggregating parts to part families, work-centers to manufacturing cells and time periods to aggregate time periods. The solution at the aggregate level is imposed as a constraint to the detailed level problem which employs a decomposition based on manufacturing cells. This architecture uses a rolling horizon strategy to perform the production management function. We have employed perturbation analysis techniques to adjust certain parameters of the optimization problems at the detailed level to reach a near- optimal detailed production plan.
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    Hierarchical Modeling Approach for Production Planning
    (1992) Harhalakis, George; Nagi, R.; Proth, J.M.; ISR
    Production management problems are complex owing to large dimensionality, wide variety of decisions of varying scope, focus and time-horizon, and disturbances. A hierarchical approach to these problems is a way to address this complexity, wherein the global problem is decomposed into a series of top-down sub- problems. We advocate that a single planning architecture cannot be employed for all planning problems. We propose a multi-layer hierarchical decomposition which is dependent on the complexity of the problem, and identify the factors influencing complexity. A systematic stepwise design approach for the construction of the hierarchy and inputs required are presented. The subsequent operation of the hierarchy in an unreliable environment is also explained. Aggregation schemes for model reduction have been developed and blended with a time-scale decomposition of activities to provide the theoretical foundation of the architecture. It is also hoped that this methodology can be applied to other such large-scale complex decision making problems.
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    Manufacturing Cell Design Using Simulated Annealing: an Industrial Application
    (1990) Harhalakis, George; Proth, J.M.; Xie, X.L.; ISR
    In this paper, we give a brief summary of simulated annealing procedures used to solve combinatorial optimization problems. We then present the manufacturing cell design problem which consists of designing cells of limited size in order to minimize inter- cell traffic. We show how to use a SA approach to obtain a good, if not optimum, solution to this problem. Finally, we apply this approach to an industrial problem and compare the results to the ones obtained using the so-called twofold heuristic algorithm.