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Division of Civil, Mechanical and Manufacturing Innovation

Operations Research  (OR)

CONTACTS

Name Email Phone Room
Edwin  Romeijn eromeijn@nsf.gov (703) 292-2211   

PROGRAM GUIDELINES

Apply to PD 10-5514 as follows:

For full proposals submitted via FastLane: standard Grant Proposal Guide proposal preparation guidelines apply.
For full proposals submitted via Grants.gov: the NSF Grants.gov Application Guide; A Guide for the Preparation and Submission of NSF Applications via Grants.gov Guidelines applies. (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 Information for Proposers

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 15-1), is effective for proposals submitted, or due, on or after December 26, 2014. The PAPPG is consistent with, and, implements the new Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (Uniform Guidance) (2 CFR 200). NSF anticipates release of the PAPPG in the Fall of 2014. Please be advised that, depending on the specified due date, the guidelines contained in NSF 15-1 may apply to proposals submitted in response to this funding opportunity.

DUE DATES

Full Proposal Window:  February 1, 2015 - February 17, 2015

February 1 - February 15, Annually Thereafter

Full Proposal Window:  September 1, 2015 - September 15, 2015

September 1 - September 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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