Mathematical Programming Methods for Logistics Planning.

Abstract

This project was concerned with the application of mathematical programming models and techniques to logistics planning problems. Basic research was performed on a new approach, called inverse optimization, to the parametric analysis of mixed integer programming models. The approach was implemented and tested for the capacitated plant location problem. Basic research was also performed on three other logistics planning models with cyclic structures; namely, lot-size problems when demand and costs are cyclic, vehicle routing and cyclic staffing. A final research effort, partially suggested by the contract, was the construction and optimization, using decomposition methods, of a model of the U.S. coal supply and demand markets.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1981
Accession Number
ADA096778

Entities

People

  • Jeremy F. Shapiro

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Civil Engineering
  • Computer Programming
  • Contracts
  • Decomposition
  • Integer Programming
  • Logistics
  • Logistics Planning
  • Massachusetts
  • Mathematical Models
  • Mathematical Programming
  • Military Research
  • Models
  • Operations Research
  • Optimization
  • Parametric Analysis
  • Scientists

Readers

  • Industrial Economics
  • Operations Research