Workforce Configuration of a Canadian Forces Gematics Division

Abstract

This paper addresses some of the pertinent issues related to the workforce configuration of a C2 organization within the Canadian Forces. The mission of the latter is to produce Geomatics Information supporting US National Imaging and Mapping Agency's (NIMA) Foundation Based Operations (FBO). Initially, the open queueing network representation of the Geomatics division (where each node or station is governed by a GI/G/s queue) is examined and its complexity analyzed. The Geomatics network belongs to the class of queueing network with signals. An alternate network architecture is proposed and the intent of which is to provide a simplified network whereby the theory of product-form solutions can be employed to evaluate the workforce configuration. The equivalence of the L norm on the waiting times between the original and the revised network is demonstrated. A nonlinear integer programming model to minimize the L norm on the waiting times for the revised network is formulated. The solution procedure involves transforming the nonlinear problem into a linear problem using approximation techniques. Fictitious data are used to illustrate the methodology.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2002
Accession Number
ADA467627

Entities

People

  • Ahmed Ghanmi
  • Kevin Y. Ng
  • M. N. Lam
  • Roy Mitchell

Organizations

  • Department of National Defence

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Command And Control
  • Computer Programming
  • Computer Science
  • Images
  • Integer Programming
  • Mathematical Models
  • Models
  • National Security
  • Operations Research
  • Pattern Recognition
  • Petri Nets
  • Probability
  • Quality Control
  • Queueing Theory
  • Simulations
  • Steady State
  • Stochastic Processes

Readers

  • Canadian European Scientific Immigration and Epilepsy Clearance Studies
  • Mathematical Modeling and Probability Theory.
  • Operations Research