A Study of Alternative Relaxation Approaches for a Manpower Planning Problem.

Abstract

This paper examines a variety of relaxation strategies for zero-one integer programming problems, containing from 54 to 2, 683 variables, that arise in manpower planning applications. These strategies are compared by a primal criterion, which emphasizes the ability to obtain high quality feasible solutions. This contrasts with the usual dual criterion for comparing relaxations, which emphasizes objective function bounds obtained from solutions that are generally not feasible. The changed emphasis requires a change in the use of relaxations, which may be viewed from the standpoint of generating trial solutions for heuristic programming or as a fundamental component of branch and bound. Computer tests show that a combined surrogate-Lagrangean strategy is the most effective for the problems examined followed by a pure surrogate relaxation strategy. All other approaches, including generalized Lagrangean relaxation, fared substantially worse, particularly in terms of solution quality. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1977
Accession Number
ADA048298

Entities

People

  • Darwin Dee Klingman
  • David Karney
  • Fred W. Glover

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computers
  • Contrast
  • Evolutionary Algorithms
  • Integer Programming
  • Linear Programming
  • Manpower
  • Mathematical Programming
  • Models
  • Naval Personnel
  • Operations Research
  • Optimization
  • Personnel Management
  • Standards
  • Systems Engineering

Readers

  • Operations Research
  • Systems Analysis and Design