Micro-Opportunistic Scheduling: The Micro-Boss Factory Scheduler

Abstract

A major challenge for research in production management is to develop new finite-capacity scheduling techniques and tools that (1) can account more precisely for actual production management constraints and objectives, (2) are better suited for handling production contingencies, and (3) allow the user to interactively manipulate the production schedule to reflect idiosyncratic constraints and preferences nor easily amenable to representation for factory scheduling currently under development at Carnegie Mellon University. Micro-Boss aims at generating and maintaining high-quality realistic production schedules by combining powerful predictive, reactive, and interactive scheduling capabilities. Specifically, the system relies on new micro-opportunistic search heuristics that enable it to constantly revise its scheduling strategy during the construction or repair of a schedule. These search heuristics are shown to be more effective than less flexible scheduling techniques proposed in the Operations Research and Artificial Intelligence Literature.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA282968

Entities

People

  • Norman Sadeh

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computations
  • Computer Science
  • Control Systems
  • Decision Support Systems
  • Gantt Charts
  • Industrial Engineering
  • Job Shop Scheduling
  • Logistics Planning
  • Manufacturing
  • Operations Management
  • Operations Research
  • Probability
  • Production
  • Scheduling (Production)
  • Systems Engineering
  • Time Intervals

Readers

  • Artificial Intelligence
  • Logistics and Supply Chain Management.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms