Cutting Some Trees to See the Forest: On Aggregation and Disaggregation in Combat Models

Abstract

Most models of air and land combat use schemes of aggregation and disaggregation in representing combat systems, in spatial configuration, and in depicting the progress of a battle. For example, the use of firepower scores is an extreme case of aggregation of weapons into a single measure. Combining like systems into weapons categories-partial aggregation-is a common approach to representing a large number of aircraft or ground weapon types. This report explores different approaches to aggregation and what is known theoretically about aggregation and disaggregation in Lanchester combat models that in two dimensions are commonly called square-law models. It defines requirements for consistency between aggregate and higher-dimensioned models of this type. Some important conclusions are that aggregation should take into account the specific capabilities of the opponent (raising concern about many 'scored' approaches that attempt to evaluate force components in isolation), and that partial aggregation (grouping 'like' systems) and disaggregation of previously aggregated results can be done consistently only when certain restrictions on the relative attrition capabilities of weapon systems hold. When this is the case, specific nonarbitrary weightings can be determined for the partial aggregations.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1993
Accession Number
ADA282392

Entities

People

  • Mario L. Juncosa
  • Richard J. Hillestad

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Defense
  • Air Force
  • Air Power
  • Aircrafts
  • Attrition
  • Computational Science
  • Differential Equations
  • Eigenvalues
  • Equations
  • Linear Differential Equations
  • Military Operations
  • National Security
  • Nonlinear Differential Equations
  • Operations Research
  • Simulations
  • Warfare
  • Weapon Systems

Readers

  • Computational Modeling and Simulation
  • Irregular Warfare and Special Operations Cyberspace Operations against Adversarial Threats.
  • Regression Analysis.