R. Agarwal, Dept. of MIS & Decision Sci., Dayton Univ., OH, USA
P. De, Dept. of MIS & Decision Sci., Dayton Univ., OH, USA
C.E. Wells, Dept. of MIS & Decision Sci., Dayton Univ., OH, USA
As more businesses move towards flexible manufacturing environments, new, techniques for factory management have begun to evolve. Of particular importance are procedures that result in detailed operational schedules to ensure that the resources of the factory are efficiently allocated. The research project outlined investigates the development of such procedures in the context of a flexible, cellular jobshop. We utilize an artificial intelligence paradigm, viz., cooperative distributed problem solving, to build a comprehensive model of the operations of a jobshop. Based on this model, detailed procedures for assigning jobs to cells, scheduling jobs on individual machines, and determining job due-dates are being developed. In addition, recognizing the uncertainties inherent in a manufacturing environment, procedures for exception handling are also being specified.
Index Terms:
flexible manufacturing systems; production control; scheduling; resource allocation; cooperative systems; problem solving; exception handling; cooperative distributed problem solving; jobshop scheduling; flexible manufacturing environments; factory management; operational schedules; resource allocation; research project; cellular jobshop; artificial intelligence paradigm; comprehensive model; scheduling; job due-dates; exception handling
Citation:
R. Agarwal, P. De, C.E. Wells, "Cooperative distributed problem solving: an investigation in the domain of jobshop scheduling," hicss, pp.4, 28th Hawaii International Conference on System Sciences (HICSS'95), 1995
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