A Convergent Aspiration Based Interior Point Method (CAIN) for Multiple Objective Linear Programming (MOLP)

Abstract

This report describes a new convergent aspiration based algorithm (CAIN--Convergent Aspiration based INterior method) for solving the multiple objective linear programming (MOLP) problem. Initial motivation for the research was provided by a recently developed methodology for the discrete multiple criteria decision making problem called AIM (Aspiration --Level Interactive model). Although CAIN uses many of the features implemented in AIM, the continuous MOLP provides for an entirely different domain of research. As part of CAIN, an innovative decision maker (DM) interaction technique called ALaRM (Aspiration Level Range Method) was concurrently developed. Using ALaRM, an interior point strategy for converging to efficient solutions is employed based upon DM levels of aspiration for the objectives. This technique, the Algorithm of Centers, has been shown to converge in polynomial time (unlike many simplex based strategies). CAIN is shown to be simple and practical from a DM standpoint, and is believed to represent an improvement over existing aspiration based MOLP techniques.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1991
Accession Number
ADA243404

Entities

People

  • M. S. Mynes

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Coefficients
  • Computational Complexity
  • Computations
  • Computer Programming
  • Computers
  • Convergence
  • Convex Sets
  • Efficiency
  • Evolutionary Algorithms
  • Goal Programming
  • Industrial Engineering
  • Linear Programming
  • Literature Surveys
  • Optimization
  • Simplex Method

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