Operations Research (Military)

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Operations Research is a scientific method to provide military decision-makers with a quantitative basis for their decisions in their area of ​​responsibility.

Although military science has provided a quantitative basis in many functions since antiquity and used the well-known mathematical methods, the term operations research was only coined by British scientists since the Second World War. At the same time, operations research (also known as corporate research ) has developed in the civil sector with its own approaches.

method

The methods of operations research can be structured and arranged according to different viewpoints, dimensions or categories. Essential categories are the type of methodology and models , application, objective, represented elements and functions of the system under consideration, as well as pragmatic categories such as user-friendliness, flexibility, portability or interfaces to other methods.

Basically, the method consists in the application of scientific foundations and principles from practically all scientific disciplines, especially mathematics, physics, economics, sociology, computer science and engineering. In particular, the provision of models, simulation with computers and Internet technology has opened new dimensions of military operations. The basic questions of Operations Research are always based on a future-oriented planning problem. For short-term periods of time, it is a matter of optimally allocating available resources and forces to tasks, missions and operations and to generate maximum impact. For long-term periods it is about the selection of technological or structural options and the best composition of forces in possible, conceivable scenarios with given investment funds. The most important scientific principles are the reproducibility of the results and the use of recognized procedures. Operations research is a cross-sectional task and can only be partially assigned to a classical scientific discipline. Since predominantly quantitative optimization and simulation methods are used, operations research is seen as a sub-discipline of mathematics and computer science.

The most important methods can be essentially distinguished in simulation and mathematical-analytical approaches. The simulation models are dynamic over time as independent parameters, the analytical methods are based on mathematical approaches, probability theory, game theory, optimization, network planning technology or statistics. The simulation models have to be differentiated according to the extent to which real components of the system to be examined are contained and whether they run deterministically or stochastically . These and other design elements result in a wide range of possible combinations that can be used in a targeted and pragmatic manner depending on the application. Military simulation games are an important and widely used method . Interactive simulations are used to take human management functions into account as realistically as possible. This is particularly important when simulating armed forces, since effectiveness is decisively influenced by the quality of military command. With mathematical-analytical models, the most important relationships in the system are known and can be treated analytically using mathematical procedures and rules. These models are comparatively abstract and not very clear for non-mathematicians, but provable solutions can be found for limited problems.

Areas of application

Models, especially simulation models, can be used for the following areas

  • Defense and structural planning
  • Development of defense material
  • Training and practice
  • Preparation and execution of operations

These basic areas of application require models that essentially represent the armed forces in terms of effectiveness and effort, but require very different applications and therefore have to be very different. For example, models for planning armed forces must permit a large number of parameter variations. At the same time, there is a relatively large amount of time available to carry out planning. In the development of defense material, it will be more a question of how the new imagined systems work in simulations in the overall network of the armed forces or which designs turn out to be optimal. When using models in training, training and exercise goals are assumed in order to train certain concepts or the interaction of many operational components. When preparing and performing operations, models are only to be used under very strict boundary conditions of the time available for processing and the available real data. When assessing the validity and validity of the procedures used, the type of application and the area of ​​application are of great importance.

Defense and structural planning has the long-term aspect of the optimal possible composition of the armed forces under many boundary conditions, above all the political specifications, resource restrictions and a spectrum of possible scenarios. The composition of the armed forces should be both cost-effective and robust, i.e. it should do justice to the tasks in as many scenarios as possible. For the use of models in planning, many scenarios have to be evaluated with many variations of parameters and structural options. The output data can only be estimated and accepted. There is generally enough time for the examinations.

The use of models in the procurement of defense material and weapon systems is about a more targeted analysis of the systems under consideration in combination with other systems in order to carry out comparisons of different concepts and to enable the functional test of imaginary drafts and prototypes in practically all phases of development . Here it will be important to consider the data and properties of the systems as precisely as possible in the models. Selected phases and detailed scenarios are generally sufficient for the investigations. Here, too, there is usually enough time to use the models.

The use of models in training has recently increased significantly, as field exercises and maneuvers are expensive, polluting and often not feasible. At the same time, there are many technical possibilities to create a virtual world for exercise participants. Here the requirements for the models are very different. On the one hand, training and exercise conditions should be as realistic as possible, and the model representation of the systems used should largely correspond to reality. On the other hand, the scenarios are accepted and should only reflect limited aspects in order to achieve certain training and exercise objectives.

The use of models to support operational staff is very diverse and affects all phases of a conceivable deployment. In any case, data is to be assumed that describe the current situation as precisely as possible. These data are contained in the existing and planned management systems that use the newer information technologies. In principle, variations in deployment options are the subject of the analyzes. The time constraints for an application are very tight. Quick and responsive analysis is usually required to meet the needs of a decision in a real-world situation.

An important aspect is the hierarchical structure of armed forces. The armed forces as a whole can be seen on the upper levels of a hierarchy and the use of individual weapon systems on the lower levels. It can be assumed from the principle that the entirety of all objects on one level can be viewed as aggregated components on the next higher level. On the other hand, the tasks and objectives of a level can be derived from the plans and objectives of the higher level. This leads to the approach of a structure of the models corresponding to the hierarchy of the armed forces. In a continuous cycle or iteration, the objectives, environmental conditions and scenarios are derived from the upper level and used as a specification for the application on the lower levels. Conversely, the results, models and methods of the lower levels serve as the basis for the applications on the higher levels.

Another important aspect when considering an armed forces system is the multiple networking of different functions of air, land and sea war with complex interactions. Many interactions can only be determined through the corresponding functions of an assumed opponent. For example, the connection between the functions of air attack and air defense can only be recognized through the corresponding functional areas of an opponent. The management function, which affects every other functional area, has proven to be very important and sensitive in all applications. The leadership is also planning, forward-looking and capable of learning, as it is perceived by people.

history

Although the term Operations Research was first coined for military purposes during the Second World War, the corresponding developments in terms of content that can be counted as part of it are already known beforehand. Examples are the engineering work in the fortress construction, the systematic cartography and navigation, the use of rule systems in war games and simulation games, up to the creation of logarithm tables for calculating trajectories. Furthermore, the work and approaches of Frederic. W. Lanchester for calculating losses and John von Neumann for game theory. Based on the experience of providing support with scientific, in particular mathematical, methods in the preparation and implementation of military operations, institutes and scientific institutions have been set up in many countries in which the methods are developed and applied. In some countries and in NATO, scientific cells are integrated directly into the higher staff in order to be immediately available to the respective leaderships. The processes, especially models and simulations, are now being developed and used with high priority in the USA and NATO. Expertise is also being systematically developed in some of the smaller NATO nations.

In Germany, the benefits of operations research were recognized early on and with the establishment of the Bundeswehr. In 1961, the Department of Defense commissioned a group of American scientists to conduct initial investigations into the structure of the Air Force. At the same time, German scientists were integrated into the group who, after a few years, were able to carry out this work autonomously. Organizationally, the group was managed as part of the Industrie Anlagen Betriebsgesellschaft (IABG) . At that time IABG was a civil law company owned by the government with the task, on the one hand, of operating systems for the German aviation industry and, on the other hand, of creating an organizational basis for the scientists in Operations Research. This basis was subsequently expanded as a study area of ​​IABG with up to 700–800 employees. From 1990 the IABG was privatized, the field of study was dissolved, the work shifted to several groups in the industry, the universities and agencies of the Bundeswehr.

literature

Web links

Individual evidence

  1. ^ Morse & Kimball
  2. ^ Klaus Niemeyer: Modeling and Simulation in Defense. In: Information & Security: An International Journal. 12, 2003, p. 19, doi : 10.11610 / isij.1201 .
  3. ↑ US Department of Defense Modeling and Simulation Coordination Office ( Memento of the original from April 21, 2009 in the Internet Archive ) Info: The archive link has been inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. @1@ 2Template: Webachiv / IABot / www.msco.mil
  4. ^ US Military Operations Research Society
  5. ↑ ncia
  6. ^ NATO Science and Technology Organization
  7. ↑ Klaus Niemeyer, Velizar Shalamanov, Todor Tagarev: Institutionalizing Operations Analysis for Security and Defense in Bulgaria. In: Connections: The Quarterly Journal. 2008, p. 45, doi : 10.11610 / Connections.07.2.04 .
  8. ↑ Reiner K. Huber: Military ORSA in Germany since the 1960s
  9. ^ Dietrich Fischer: Military Operations Research (OR) in Germany: the beginnings
  10. ↑ Thilo Wedlich: The History of the Military Operations Research's / system analysis in Germany
  11. ^ IABG
  12. ↑ Institute for Technology of Intelligent Systems (ITIS) ( Memento of the original from November 19, 2016 in the Internet Archive ) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. @1@ 2Template: Webachiv / IABot / www.unibw.de
  13. ↑ Planning Office of the Bundeswehr