My notes on Contested Logistics
I have compiled notes from RAND Corporation’s Future Logistics Concept Assessment Framework and tied the framework to a recently published Contested logistics simulation output analysis with approximate dynamic programming by MITRE Corporation. The views expressed are those of the author and do not reflect the official policy or position of the US Air Force, Department of Defense or the US Government.
Future Logistics Concept Assessment Framework
RAND Corporation recently published the Future Logistics Concept Assessment Framework, which is a disciplined, systematic way to assess proposed future logistics concepts to meet the requirements of the National Defense Strategy (NDS). In order to meet the NDS, Air Force logistics needs to assess the concept framework into a variety of scenarios, and implement the concept framework to doctrine, organization, training, materiel, leadership and education, personnel, facilities, and policy (DOTMLPF-P).
The AFDN 1–21, Agile Combat Employment, codifies a proactive and reactive operational scheme of maneuver to increase survivability while generating combat power throughout the integrated deterrence continuum. Our services must successfully develop multi-capable Airmen that will deploy, survive, operate, maneuver, and regenerate in all domains while under attack. The NDS calls for dynamic force employment, which means that employment of forces should be proactive and scalable, theater postures should be flexible, and forces should be readily maneuverable.
The U.S. Air Force logistics must be postured for expeditionary operations with geographically extended logistics supply lines potentially operating for a protracted duration against near-peer adversaries. Additionally, the Air Force must develop the ability to prosecute logistics operations in a nuclear, chemical, or biological environment. Finally, the Air Force must prepare for the possibility of attacks on the U.S. homeland, including commercial logistics support entities.
One of the most determinative factors with respect to the demand on logistics is the size of the deployed force and the operations tempo — the intensity of a potential conflict. Iraq and Afghanistan capture the logistics requirements of a medium- to low-intensity conflict. However, a long duration high-end fight is plausible in a future warfighting scenario against near-peer adversaries who will aim at seizing the initiative, confusing the enemy, and establishing control of the battlespace such that follow-on forces can surge into the theater.
Adversaries will utilize horizontal (geographic) and vertical (intensity) escalation of conflict that will most likely lead to a future conflict which may not stay contained within a single region, as the U.S. forces continues to extend deterrence and security commitments. Therefore, the United States must partner with allied forces to deter conflict and prevail in the event that deterrence fails. In a situation in which timeliness could decide the intensity, duration, or outcome of a conflict, swiftly obtaining an ally’s approval to provide access could be determinative. In terms of the threat environment, the Air Force must prepare for conventional (guided missiles/bombs), unconventional (EW/cyber), insider, chemical, biological, and nuclear threats. Demands that better the future logistics concept include the capability to operate out of locations without runways, the need to operate out of a large number of locations, and the need to be mobile.
DOTMLPF-P: Doctrine, Organization, Training, Materiel, Leadership and Education, Personnel, Facilities, and Policy
For most future logistics concepts, many different organizations will need to play a role for the concept to be successfully developed and fielded. Implementing a future logistics concept will involve a large, diverse, complex, and often unwieldy enterprise. Table below depicts the organizations that are expected to play a role in the concept’s implementation.
For doctrine, existing doctrine may need to adapt to future logistics concept to meet changes at the joint level. For training, future logistics concept may affect existing training, affect cross-training, or require a whole new training course.
For materiel, any new concepts must have general estimate of Technology Readiness Level (TRL) to alert decisionmakers of the technological risk the concept might carry. For new technologies, acquisition strategies such as off the shelf (commercial), Urgent Operational Need, Joint Urgent Operational Need (JUON), Section 804 Authorities (Rapid Prototyping), or Other Transaction Authorities (OTAs) should be best utilized for each new concept. Existing legacy materiel such as communication nodes will need to meet specific communication needs and increase the data rate across existing communication channels.
For leadership and education, future logistics concept must account for command and control reporting relationships in regards to centralized and decentralized decision making authority. For personnel, future logistics concept could require additional personnel such as contractors and partner nation support, while also accounting for new authorization levels, new positions or job titles, or new Air Force Specialty Codes. For facilities, future logistics concepts may require changes at the home station or at deployed locations, including any facilities for storage or in-transit support. For policy, future logistics concept may need to account for changes in Tactics, techniques, and procedures (TTP) to meet joint, interagency, coalition, U.S., or international law or regulations.
DOTMLPF-P is not just utilized for the Air Force, but all services. And the efforts of Agile Combat Employment is being tested by all forces. The Navy is working on distributed maritime operations, from concentrated power on a single carrier strike group. The Army is building multi-domain task force units of air defense, cyber and rocket artillery systems that act as mobile fortresses. And the Marine Corps is posturing for a more agile and lethal Marine Air-Ground Task Force (MAGTF) driven by data that will sustain combat power in contested environments.
Case Study — Project Pele
One future logistics concept from RAND corporation is the deployment of very Small Modular Reactors (vSMRs) which will serve as a reliable power source for deployed locations, also known as Project Pele. Micro-reactors will produce 1–10 megawatts and serve the purpose of reducing dependency on host-nation power and supply lines for fossil fuels for diesel generators, while also providing more power to support potential future systems, such as directed energy weapons, which might have high energy demands. Ultimately, vSMRs will increase the versatility of maneuver for fielding of attritable aircraft and directed energy weapons for Evolving Blue Concepts of Employment (Blue CONEPS).
To implement vSMRs, the A4 staffs at Headquarters U.S. Air Force (HAF) will need to partner with allies for joint doctrine with Air Force. Air Combat Command will organize, train, and equip U.S. Air Force forces on special nuclear materials in the day-to-day operations. Air Mobility Command will need to provide rapid, global mobility and sustainment via new flight procedures that will ensure the safe transport of a vessel containing radioactive materials, similar to the 62nd Airlift Wing’s Prime Nuclear Airlift Force.
Air Force Materiel Command will be responsible for the development, acquisition, and life cycle management of vSMRs. Finally, Air Force Global Strike Command and the Deputy Chief of Staff for Strategic Deterrence and Nuclear Integration (AF/A10) will develop a plan in response to the event that a forward deployed vSMR is targeted with a kinetic strike. Other entities include the Defense Logistics Agency for disposition of materials and the Defense Threat Reduction Agency for accident or intentional strike on a vSMR.
This new concept is one of many future logistics concepts that can be optimized for a variety of scenarios and be implemented for DOTMLPF-P. Future decision-makers will rely on new technologies including advanced computing, “big data” analytics, and artificial intelligence (AI), setting an ever greater significance on Information and cyber warfare. One such case is Contested logistics simulation output analysis from MITRE corporation.
Contested Logistics Simulation with approximate dynamic programming
Current, near peer, adversarial applications of lethal and nonlethal anti-access/area-denial (A2/AD) capabilities expand contested logistic environments and potentially impact mission success. As such, if aerial and seaports of debarkation (A/SPOD) are denied, then strategic or operationally distant maneuvering may be required, which further complicates logistic operations. Therefore, simulations are tested to assess joint interoperability, adversarial deterrents, or validating plans.
MITRE Corporation’s simulation using SIMIO displays supported unit (TF1) and a supporting aerial port are located within an area of responsibility (AOR) that is vulnerable to red adversary Dong–Feng 21 (DF-21) medium-range ballistic missile launchers. Aerial port operations are defined by velocity and volume of supplies needed for TF1. TF1 moves deeper into adversary territory, becoming vulnerable to additional red units, artillery and air defense artillery (ADA). The aerial port must depart its current location at edge port 1 (EP1) and routinely move to other EPs inside the AOR to avoid DF-21 targeting while continuing logistics support. The goal of the simulation is to calculate potential aerial port location should the EP move, what type of transportation should the EP use to get there, and how should the EP perform resupply logistic support operations to TF1 at its new location.
With 19 potential aerial port locations, 7 possible movement combination options of aircraft, ship or truck and 7 possible resupply combination options of drone, ship or truck yielded 931 options with different costs and distances, resupply costs and distances and threat vulnerability. With learning reinforcement (Q-learning) using random interactions within a dynamic environment and reward-based performance evaluation, the model became a prototype for making approximately optimal decisions in a rapidly changing operational environment.
The military recognizes AI as a necessary resource to keep pace with near-peer adversaries, yet stubbornly sticks to decision-making processes that do not adapt to dynamic environments over lengthy horizons.
