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This paper presents a method to quantify the value of reconnaissance for both direct and indirect fire weapons for the defense-in-sector battle scenario. The Lanchester area fire model and the Helmbold equations were modified to allow the lethality of the defending blue force to be increased as they gained more combat intelligence about the attacking red force, thus modeling intelligence as a true combat multiplier. By adjustments made to parameters in the model, the lethality of blue direct and indirect fire weapons could be adjusted based on the quantity and quality of their intelligence assets. With information from a computer database, and the COMAN model, maximum likelihood attrition rate estimates were calculated for both red and blue forces for ten heavy defensive battles conducted at the Army's National Training Center. In each battle, the red force attrition rate was fitted to a curve which represented a percentage of blue's full potential, represented here by the square law. Using this model in a combat simulation, and with some preliminary work with comparable systems, one could implement a change in blue's intelligence assets and then provide a quantitative measure of the effect that this had on the outcome of a battle.
Quantifying the war fighting value of reconnaissance is a hard problem. Standard analytical techniques fail to identify second and higher order effects of reconnaissance when integrated in a combat model. Additionally, current simulation techniques fail to model the human factor in information transfer and decision making. Finally, conventional measures of effectiveness concentrating on attrition (loss exchange ratios, killer/victim scoreboards, etc.) are clearly inadequate when tasked to measure reconnaissance effectiveness. This study attempts to answer the question of how to quantify the value of reconnaissance. We first examine the role of reconnaissance in the battle process, to include defining reconnaissance and conducting a task/mission analysis. Next, we explore a potential methodology for Army analysts to use in quantifying the value of new reconnaissance systems, doctrine, or force structures. Lastly, this paper chronicles several ongoing efforts to validate and refine this proposed methodology.
A report by the Dept. of Defense¿s Command and Control Research Program. Contents: (1) Complexity in Natural and Economic Systems; (2) Concepts for Warfare from Complexity Theory; (3) Evidence for Complex Emergent Behavior in Historical Data; (4) Mathematical Modeling of Complexity, Knowledge, and Conflict; (5) An Extended Example of the Dynamics of Local Collaboration and Clustering, and Some Final Thoughts. Appendix: Optimal Control with a Unique Control Solution. Tables and figures.
This document reports on a small set of information-age measures of effectiveness (MOEs) for the Army, developed in an attempt to spark the creation of more measures. The research shows that development of MOEs is feasible, not only for combat operations but for stability operations too.
Addresses the challenges of this changed world, the difficulties for defense planning these challenges engender, and new analytic techniques for framing these complex problems.
Operations Research (OR) emerged in an effort to improve the effectiveness of newly inducted weapons and equipment during World War II. While rapid growth ofOR led to its becoming an important aid to decision making in all sectors including defense, its contribution in defense remained largely confined to classified reports. Very few books dealing with applications of quantitative decision making techniques in military have been published presumably due to limited availability ofrelevant information. The situation changed rapidly during the last few years. The recognition of the subject of Military Operations Research (MOR) gave tremendous boost to its development. Books and journals on MOR started appearing. The number of sessions on MOR at national and international conferences also registered an increase. The volume of teaching, training and research activities in the field of MOR at military schools and non-military schools enhanced considerably. Military executives and commanders started taking increasing interest in getting scientific answers to questions pertaining to weapon acquisition, threat perception and quantification, assessment of damage or casualties, evaluation of chance of winning a battle, force mix, deployment and targeting of weapons against enemy targets, war games and scenario evaluation. Most of these problems were being tackled on the basis of intuition, judgment and experience or analysis under very simple assumptions. In an increasingly sophisticated and complex defense scenario resulting in advances in equipment and communications, the need for supplementing these practices by scientific research in MOR became imperative.
Joint Vision 2020 is the conceptual template for how we will channel the vitality of our people and leverage technological opportunities to achieve new levels of effectiveness in joint warfighting.