Optimization and Persistence

Abstract

Most optimization-based decision support systems are used repeatedly with only modest changes to input data from scenario to scenario. Unfortunately, optimization (mathematical programming) has a well-deserved reputation for amplifying small input changes into drastically different solutions. A previously optimal solution, or a slight variation of one, may still be nearly optimal in a new scenario and managerially preferable to a dramatically different solution that is mathematically optimal. Mathematical programming models can be stated and solved so that they exhibit varying degrees of persistence with respect to previous values of variables, constraints, or even exogenous considerations. We use case studies to highlight how modeling with persistence has improved managerial acceptance and describe how to incorporate persistence as an intrinsic feature of any optimization model.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1997
Accession Number
ADA576179

Entities

People

  • Gerald G. Jerry Brown
  • R. Kevin Wood
  • Robert F. Dell

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Base Closures
  • Case Studies
  • Coast Guard
  • Decision Support Systems
  • Gantt Charts
  • Helicopters
  • Linear Programming
  • Logistics
  • Mathematical Models
  • Mathematical Programming
  • New York
  • Nonlinear Programming
  • Operations Research
  • Optimization
  • Production Engineering

Readers

  • Computational Modeling and Simulation
  • Operations Research
  • Systems Analysis and Design