Operations Research  (OR)

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PROGRAM GUIDELINES

Apply to PD 10-5514 as follows:

For full proposals submitted via FastLane: standard Grant Proposal Guidelines apply.
For full proposals submitted via Grants.gov: NSF Grants.gov Application Guide; A Guide for the Preparation and Submission of NSF Applications via Grants.gov Guidelines apply (Note: The NSF Grants.gov Application Guide is available on the Grants.gov website and on the NSF website at: http://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide)

Important Notice to Proposers

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG), NSF 13-1, was issued on October 4, 2012 and is effective for proposals submitted, or due, on or after January 14, 2013. Please be advised that, depending on the specified due date, the guidelines contained in NSF 13-1 may apply to proposals submitted in response to this funding opportunity.

Please be aware that significant changes have been made to the PAPPG to implement revised merit review criteria based on the National Science Board (NSB) report, National Science Foundation's Merit Review Criteria: Review and Revisions. While the two merit review criteria remain unchanged (Intellectual Merit and Broader Impacts), guidance has been provided to clarify and improve the function of the criteria. Changes will affect the project summary and project description sections of proposals. Annual and final reports also will be affected.

A by-chapter summary of this and other significant changes is provided at the beginning of both the Grant Proposal Guide and the Award & Administration Guide.

DUE DATES

Full Proposal Window:  September 1, 2013 - October 1, 2013

September 1 - October 1, Annually Thereafter

Full Proposal Window:  January 15, 2014 - February 15, 2014

January 15 - February 15, Annually Thereafter

Due dates repeat annually. Please reference the CMMI main page for further specifics concerning unsolicited proposal submission windows.

SYNOPSIS

The OR program supports fundamental research leading to the creation of innovative mathematical models, analysis, and algorithms for optimal or near optimal decision-making, applicable to the design and operation of manufacturing, service, and other complex systems. In addition to the traditional areas of Operations Research which includes discrete and continuous optimization as well as stochastic modeling and analysis, new research thrusts include simulation optimization and self-optimizing systems that can observe, learn, and adapt to changing environments.

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THIS PROGRAM IS PART OF

Systems Engineering and Design

What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)

Map of Recent Awards Made Through This Program

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