Search NASA⌕ Search

SEARCH · Search NASA

Results for “integrated planning and scheduling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

The entropy reduction engine: Integrating planning, scheduling, and control

The Entropy Reduction Engine, an architecture for the integration of planning, scheduling, and control, is described. The architecture is motivated, presented, and analyzed in terms of its different components; namely, problem reduction, temporal projection, and situated control rule execution. Experience with this architecture has motivated the recent integration of learning. The learning methods are described along with their impact on architecture performance.

Drummond, Mark↗
NASA NTRS1992

Coordinating space telescope operations in an integrated planning and scheduling architecture

The Heuristic Scheduling Testbed System (HSTS), a software architecture for integrated planning and scheduling, is discussed. The architecture has been applied to the problem of generating observation schedules for the Hubble Space Telescope. This problem is representative of the class of problems that can be addressed: their complexity lies in the interaction of resource allocation and auxiliary task expansion. The architecture deals with this interaction by viewing planning and scheduling as two complementary aspects of the more general process of constructing behaviors of a dynamical system. The principal components of the software architecture are described, indicating how to model the structure and dynamics of a system, how to represent schedules at multiple levels of abstraction in the temporal database, and how the problem solving machinery operates. A scheduler for the detailed management of Hubble Space Telescope operations that has been developed within HSTS is described. Experimental performance results are given that indicate the utility and practicality of the approach.

Muscettola, Nicola↗
NASA NTRS1995

Integrated planning and scheduling for Earth science data processing

Several current NASA programs such as the EOSDIS Core System (ECS) have data processing and data management requirements that call for an integrated planning and scheduling capability. In this paper, we describe the experience of applying advanced scheduling technology operationally, in terms of what was accomplished, lessons learned, and what remains to be done in order to achieve similar successes in ECS and other programs. We discuss the importance and benefits of advanced scheduling tools, and our progress toward realizing them, through examples and illustrations based on ECS requirements. The first part of the paper focuses on the Data Archive and Distribution (DADS) V0 Scheduler. We then discuss system integration issues ranging from communication with the scheduler to the monitoring of system events and re-scheduling in response to them. The challenge of adapting the scheduler to domain-specific features and scheduling policies is also considered. Extrapolation to the ECS domain raises issues of integrating scheduling with a product-generation planner (such as PlaSTiC), and implementing conditional planning in an operational system. We conclude by briefly noting ongoing technology development and deployment projects being undertaken by HTC and the ISTB.

Boddy, Mark↗
DOE OSTI2021

Data-driven optimization of mixed-integer bi-level multi-follower integrated planning and scheduling problems under demand uncertainty

The coordination of interconnected elements across the different layers of the supply chain is essential for all industrial processes and the key to optimal decision-making. Yet, the modeling and optimization of such interdependent systems are still burdensome. Here we address the simultaneous modeling and optimization of medium-term planning and short-term scheduling problems under demand uncertainty using mixed-integer bi-level multi-follower programming and data-driven optimization. Bi-level multi-follower programs model the natural hierarchy between different layers of supply chain management holistically, while scenario analysis and data-driven optimization allow us to retrieve the guaranteed feasible solutions of the integrated formulation under various demand considerations. We address the data-driven optimization of this challenging class of problems using the DOMINO framework, which was initially developed to solve single-leader single-follower bi-level optimization problems to guaranteed feasibility. This framework is extended to solve single-leader multi-follower stochastic formulations and its performance is characterized by well-known single and multi-product process scheduling case studies. Through our data-driven algorithmic approach, we present guaranteed feasible solutions to linear and nonlinear mixed-integer bi-level formulations of simultaneous planning and scheduling problems and further characterize the effects of the scheduling level complexity on the solution performance, which spans over several hundred continuous and binary variables, and thousands of constraints.

42 ENGINEERING↗
NASA NTRS1992

Completable scheduling: An integrated approach to planning and scheduling

The planning problem has traditionally been treated separately from the scheduling problem. However, as more realistic domains are tackled, it becomes evident that the problem of deciding on an ordered set of tasks to achieve a set of goals cannot be treated independently of the problem of actually allocating resources to the tasks. Doing so would result in losing the robustness and flexibility needed to deal with imperfectly modeled domains. Completable scheduling is an approach which integrates the two problems by allowing an a priori planning module to defer particular planning decisions, and consequently the associated scheduling decisions, until execution time. This allows a completable scheduling system to maximize plan flexibility by allowing runtime information to be taken into consideration when making planning and scheduling decision. Furthermore, through the criteria of achievability placed on deferred decision, a completable scheduling system is able to retain much of the goal-directedness and guarantees of achievement afforded by a priori planning. The completable scheduling approach is further enhanced by the use of contingent explanation-based learning, which enables a completable scheduling system to learn general completable plans from example and improve its performance through experience. Initial experimental results show that completable scheduling outperforms classical scheduling as well as pure reactive scheduling in a simple scheduling domain.

Gervasio, Melinda T.↗
NASA NTRS2018

Integrated Planning and Scheduling for NASA’s Deep Space Network – from Forecasting to Real-time

Over a period of several years, the software systems that plan and schedule the use of NASA’s Deep Space Network (DSN) for the projects it serves have been upgraded from a disparate set of decades-old software components, to an integrated suite covering long-range planning and forecasting, all the way to real-time scheduling. The most recent component of this suite is known as LAPS, for Loading Analysis and Planning Software, and is responsible for long-term planning and forecasting, including studies and analysis of new missions, changed mission requirements, downtime, and new or changed antenna capabilities. This paper discusses the architecture of LAPS and its interfaces with other elements of DSN planning and scheduling, its user interfaces, and some lessons learned from development and deployment.

Lad, Jigna↗
NASA NTRS1992

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques.

Drummond, Mark↗
NASA NTRS1994

Constraint-based integration of planning and scheduling for space-based observatory management

Progress toward the development of effective, practical solutions to space-based observatory scheduling problems within the HSTS scheduling framework is reported. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) short-term observation scheduling problem. The work was motivated by the limitations of the current solution and, more generally, by the insufficiency of classical planning and scheduling approaches in this problem context. HSTS has subsequently been used to develop improved heuristic solution techniques in related scheduling domains and is currently being applied to develop a scheduling tool for the upcoming Submillimeter Wave Astronomy Satellite (SWAS) mission. The salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research are summarized. Then, some key problem decomposition techniques underlying the integrated planning and scheduling approach to the HST problem are described; research results indicate that these techniques provide leverage in solving space-based observatory scheduling problems. Finally, more recently developed constraint-posting scheduling procedures and the current SWAS application focus are summarized.

Muscettola, Nicola↗
NASA NTRS1992

An application of artificial intelligence to automatic telescopes

Automatic Photoelectric Telescopes (APT's) allow an astronomer to be removed form the telescope site in both time and space. APT's 'execute' an observation program (a set of observation requests) expressed in an ASCII-based language (ATIS) and collect observation results expressed in this same language. The observation program is currently constructed by a Principal Astronomer from the requests of multiple users; the execution is currently controlled by a simple heuristic dispatch scheduler. Research aimed at improving the use of APT's is being carried out by the Entropy Reduction Engine (ERE) project at NASA Ames. The overall goal of the ERE project is the study and construction of systems that integrate planning, scheduling, and control. This paper discusses the application of some ERE technical results to the improvement of both the scheduling and the operation of APT's.

Swanson, Keith↗
NASA NTRS1990

Integrating planning and reaction: A preliminary report

The Entropy Reduction Engine architecture for integrating planning, scheduling, and control is examined. The architecture is motivated through a NASA mission scenario and a brief list of design goals. An overview is presented of the Entropy Reduction Engine architecture by describing its major components, their interactions, and the way in which these interacting components satisfy the design goals.

Bresina, John L.↗
NASA NTRS2005

MSL Project Update

Mars Science Lab (MSL) Project activities over the last 3-4 months focused on: a) Payload accommodation; b) Flight system architecture definitization; c) Program architecture support. Baseline project concept is to develop and fly two identical vehicles with launches in 2009 and 2011: a) Significant programmatic uncertainty remains due to NASA strategic issues (Shuttle Return to flight, Hubble servicing, CEV, etc.); b) Final "decisions" on future program not likely for 3-4 months; c) To maintain viability for a 2009 launch, the project must rapidly move into implementation mode despite this uncertainty. Near term activities: a) Converge baseline flight system architecture & instrument accommodation - June; b) Instrument accomodation reviews (IARs) are completed for DAN, MSSS instruments; c) Develop project-wide implementation plan & integrated schedule - June; d) Conduct grassroots cost exercise - July/August; e) Hold Preliminary Mission System Review - September.

Mars↗
DOE OSTI2022

Integrated charging infrastructure planning and charging scheduling for battery electric bus systems

We report studies on the electric bus system planning problem have typically focused exclusively on either the deployment of charging infrastructure or the scheduling of charging events; few have examined the impact of charging facility deployment on charging activities. Considering the interdependence of system design and operational strategies, this study proposes a two-phase optimization framework for charging infrastructure planning and charging scheduling for battery electric bus systems. An integrated optimization model is first developed to simultaneously optimize charger deployment, on-board battery capacity, and charging schedules. A charging scheduling model is further proposed and a rolling horizon approach is utilized in the second phase to optimize the real-time charging scheduling of electric buses. Compared to existing electric bus system planning methods, the proposed integrated model can reduce the total system cost by 19.5%. In addition, compared to uncontrolled charging, the proposed rolling horizon-based charging strategy can reduce the total charging cost by 68.3%.

25 ENERGY STORAGE↗
NASA NTRS1994

Autonomous mission planning and scheduling: Innovative, integrated, responsive

Autonomous mission scheduling, a new concept for NASA ground data systems, is a decentralized and distributed approach to scientific spacecraft planning, scheduling, and command management. Systems and services are provided that enable investigators to operate their own instruments. In autonomous mission scheduling, separate nodes exist for each instrument and one or more operations nodes exist for the spacecraft. Each node is responsible for its own operations which include planning, scheduling, and commanding; and for resolving conflicts with other nodes. One or more database servers accessible to all nodes enable each to share mission and science planning, scheduling, and commanding information. The architecture for autonomous mission scheduling is based upon a realistic mix of state-of-the-art and emerging technology and services, e.g., high performance individual workstations, high speed communications, client-server computing, and relational databases. The concept is particularly suited to the smaller, less complex missions of the future.

Sary, Charisse↗
NASA NTRS1991

The APT/ERE planning and scheduling manifesto

The Entropy Reduction Engine, ERE project, is focusing on the construction of integrated planning and scheduling systems. Specifically, the project is studying the problem of integrating planning and scheduling in the context of the closed loop plan use. The results of this research are particularly relevant when there is some element of dynamism in the environment, and thus some chance that a previously formed plan will fail. After a preliminary study of the APT management and control problem, it was felt that it presents an excellent opportunity to show some of the ERE Project's technical results. Of course, the alignment between technology and problem is not perfect, so planning and scheduling for APTs presents some new and difficult challenges as well.

Drummond, Mark↗
NASA NTRS2015

Integrating Human Performance Measures into Space Operations: Beyond Our Scheduling Capabilities?

Current planning and scheduling software tools for International Space Station (ISS) support different flight controller teams as they plan daily space operations. Planning and scheduling tools capabilities include integrating digitized ISS state inputs, evaluating their expected future states, and propagating them over time. Extensive, custom-made computational models of operations, of objectives, and of operational constraints help ISS flight controllers identify where scheduled events violate constraints. Based on the current capabilities of these tools, this paper proposes how human performance measures could be better integrated into planning and scheduling tools for space mission operations. Future integration of human performance measures could be applied to state inputs (in this case, the astronaut’s state) and to modeling human performance operational constraints & operational objectives (i.e., assigned activities) with parameters that are relevant to human performance measures. Gaps between the state-of-the-art for human performance modeling and planning tools for future exploration missions are identified.

space operations↗
NASA NTRS2005

Automated Planning and Scheduling for Space Mission Operations

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

scheduling↗