Knowledge-Based Logistics Planning: Its Application in Manufacturing and Logistics Planning.
Final rept. Jan 91-Jun 94,
CARNEGIE-MELLON UNIV PITTSBURGH PA
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This document summarizes research in CORTES, a project in constraint-based planning, scheduling, and control for complex large-scale domains such as military transportation and manufacturing. The CORTES approach keeps the planningscheduling combinatories in check, using quantitative problem space metrics called texture measures to 1 identify critical decisions that require early attention and 2 steer search toward promising solutions. This basic approach has been applied and validated in several key contexts, including 1 micro-opportunistic search, which focuses on efficient generation and dynamic maintenance of complex large-scale Just-In-Time schedules 2 simulated annealing search, where texture measures have been developed to focus search and learn to recognize unpromising runs 3 iterative constraint posting, which combines flexible schedule representation and dynamic identification of conflicts requiring further arbitration 4 integration of predictive planning scheduling and execution control, where texture measures and flexible schedule representations are combined to coordinate multiple planningscheduling and control agents and 5 Interactive schedule repair, where adaptive similarity metrics direct re-use of previous repair histories and help select repair focus and actions. Visualization issues have been addressed by developing comprehensive see reverse languages for characterizing 1 domain concepts to be displayed 2 user analysis tasks and 3 graphical presentation techniques that can be assembled to create displays. MM
- Administration and Management
- Logistics, Military Facilities and Supplies