The Office of Naval Research (ONR) Mathematical Optimization program supports basic research in optimization—focusing on the development of theory and algorithms for large-scale optimization problems. Application-driven research in optimization is supported by the Resource Optimization thrust under the Computational Methods for Decision Making program.
The primary focus of the Mathematical Optimization program is the development of new, cutting-edge theory and algorithms for efficiently solving problems in linear, nonlinear, integer and combinatorial optimization. Theoretical development, algorithmic design and analysis, computational methods, and software prototypes for large-scale problems are of interest. This directive includes, but is not limited to, cutting plane and polyhedral techniques for mixed-integer programming, decomposition approaches for large (non)convex problems, and interior-point and first-order algorithms for conic/convex optimization. Advances that produce provably optimal or near-optimal solutions, as well as those applicable to large problem domains, are favored. Innovative strategies for dealing with uncertainty from stochastic optimization, robust optimization and simulation-based optimization are of growing interest. Research supported by this program is expected to make fundamental contributions to the field of mathematical optimization.
Proposers to the Mathematical Optimization program are encouraged to contact the program manager to discuss research interests and to submit a white paper prior to the submission of a formal proposal. White papers are pre-proposals, approximately four pages in length, that summarize the proposed research and scientific contributions to the field of optimization. They should be submitted by email to the program manager each year by May 1. Based on the white paper, and upon such considerations as quality of research, reviews, compatibility with the program and anticipated budget, requests will be made for formal proposals.
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