New Models for Utilizing Extracted Legacy System Data in Extended-Enterprise Decisions Support Systems

    Our research focuses on optimal schedule coordination for multiple firms collaborating on a joint production or construction project over a relatively short period of time.  This work applies primarily to contexts in which different firms must work together to complete a made-to-order product or structure, but where no formal relationship or virtual integration (e.g., standardized communications infrastructure) exists between the firms.  These firms face the challenge of effectively coordinating multiple interdependent tasks by scheduling these tasks to ensure timely and cost-effective completion of the project.  More often than not, the firms have disparate and incompatible information systems, which inhibit effective schedule coordination.

Using data extracted from legacy systems via the SEEK platform, we propose new models and solution algorithms for resource and project scheduling among multiple firms.  We initially focus on the single-participant resource scheduling problem: given a set of jobs to be performed by the firm, along with critical firm-specific information and parameters extracted from the firm’s legacy system (e.g., resource capabilities, job processing requirements, overtime options, and job tardiness costs), determine the optimal job sequence and overtime usage for the firm’s resources.  We are currently working to expand the scope of this class of problems to account for uncertainty in the firm’s total job processing requirements.  Upon solving each firm’s resource scheduling problem, we will then focus on solving the global project scheduling problem: given each firm’s resource availability and constraints, and the interdependence among jobs to be performed by the different firms, determine the start and finish times for each task required for project completion at minimum total project cost.