Combining AI and OR in Heuristics and Optimization

Abstract

Mixed logical/linear programming (MLLP) was developed as an extension of mixed integer/linear programming. What appears to be the first practical method of sensitivity analysis for mixed integer/linear programming was developed and applied to a Proctor and Gamble supply chain problem. Consistency-achieving methods of constraint programming were linked with constraint generation methods in operations research. Continuous relaxations were identified for mixed discrete/continuous optimization problems that can accelerate their solution within a logic-based approach. A research monograph, Logic-Eased Methods for Optimization, was written.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1997
Accession Number
ADA388049

Entities

People

  • John N. Hooker

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computer Programming
  • Computer Science
  • Consistency
  • Integer Programming
  • Linear Programming
  • Mathematical Programming
  • Operations Research
  • Optimization
  • Sensitivity
  • Supply Chain
  • Supply Chain Management
  • Trees (Data Structures)

Readers

  • Artificial Intelligence
  • Operations Research