To support an Effects Based Approach to Operations (EBAO), Intelligence, Surveillance, and Reconnaissance (ISR) planners must optimize collection plans within an evolving battlespace. A need exists for a decision support tool that allows ISR planners to rapidly generate and rehearse high-performing ISR plans that balance multiple objectives and constraints to address dynamic collection requirements for assessment. To meet this need we have designed an evolutionary algorithm (EA)-based "Integrated ISR Plan Analysis and Rehearsal System" (I2PARS) to support Effectsbased Assessment (EBA). I2PARS supports ISR mission planning and dynamic replanning to coordinate assets and optimize their routes, allocation and tasking. It uses an evolutionary algorithm to address the large parametric space of route-finding problems which is sometimes discontinuous in the ISR domain because of conflicting objectives such as minimizing asset utilization yet maximizing ISR coverage. EAs are uniquely suited for generating solutions in dynamic environments and also allow user feedback. They are therefore ideal for "streaming optimization" and dynamic replanning of ISR mission plans. I2PARS uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to automatically generate a diverse set of high performing collection plans given multiple objectives, constraints, and assets. Intended end users of I2PARS include ISR planners in the Combined Air Operations Centers and Joint Intelligence Centers. Here we show the feasibility of applying the NSGA-II algorithm and EAs in general to the ISR planning domain. Unique genetic representations and operators for optimization within the ISR domain are presented along with multi-objective optimization criteria for ISR planning. Promising results of the I2PARS architecture design, early software prototype, and limited domain testing of the new algorithm are discussed. We also present plans for future research and development, as well as technology transition goals.
The Joint Assistant for Deployment and Execution (JADE) offers a new technique for rapid force deployment planning, especially in crisis situations. JADE is being developed by BBN Technologies under contract to the Air Force Research Lab and the Defense Advanced Research Projects Agency (DARPA). It is being designed to operate within the next generation Global Command and Control System. JADE implements state of the art technology to reduce the time typically required for building a Time Phased Force Deployment Data package, which presently takes days or weeks, down to approximately one hour. In order to support the command and control needs of planners today and in the twenty-first century, several challenges are being met to transition JADE from a research prototype to a fully operational system. These include integrating various data systems, seeking user input and buy-in, porting to new computing environments, assuring compliance with the Defense Information Infrastructure Common Operating Environment, and testing in exercise scenarios. A potential technology transition candidate for JADE is the Adaptive Course of Action (ACOA) program. ACOA is a DARPA advanced conceptual technology demonstration (ACTD) that provides the means to employ new technologies in the Joint Operations Planning and Execution environment. The ACOA tool suite is also a key enabler in achieving Joint Vision 2010. In this paper, a detailed overview of JADE is provided along with plans for technology transition. JADE OverviewJADE demonstrates breakthrough technology that enables a military planner to build a force deployment plan, including a Time Phased Force Deployment Data (TPFDD) package in less than one hour. JADE is a knowledge-intensive planning technique that employs case-based and generative planning methods to handle large-scale, complex plans in minimal time. The tool is capable of rapid retrieval and reuse of previous plan elements and employs an easy to use maporiented drag and drop interface. Force modules from previous plans whose force capabilities and composition satisfy the current situation can be dragged from the plan library (casebase) and
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