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Advanced Algorithm Development for Mission Planning

Active

Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The contract focuses on the development and validation of advanced optimization algorithms specifically designed for naval mission planning. This involves creating solutions for dynamic resource allocation, pathfinding, and distributed decision-making processes under uncertainty, utilizing modeling and simulation techniques. The goal is to enhance mission effectiveness by improving how resources are assigned and paths are determined in complex, changing environments. Issued by the Office of Naval Research under the Department of Defense, the contract is categorized as a subcontract related to the NAICS code 541715, which pertains to research and development in the physical, engineering, and life sciences. Although specific location details and points of contact are not provided, the work involves sophisticated algorithmic development aimed at supporting naval operations through improved planning tools.

General Info

Development of advanced optimization algorithms for naval mission planning, resource allocation, and decision-making.

Agency

Department Of Defense → Office Of Naval Research

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology) View NAICS

Place of Performance

VA

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

PostedMay 11

subcontract

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Organization & Contact Information

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AgencyDepartment Of Defense → Office Of Naval Research

ContactsNo contacts available

OfficeN/A

Organization / Agency

Department Of Defense → Office Of Naval Research

Office AddressN/A

ContactsNo contact information available

Full Description

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Develop and validate optimization algorithms for naval mission planning, including dynamic resource allocation, pathfinding, and distributed decision-making under uncertainty using modeling and simulation.

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