A mixed-integer PDE-constrained optimization formulation for constructing electromagnetic cloaks with multiple materials

Ryan H. Vogt (), Sven Leyffer () and Todd Munson ()
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Ryan H. Vogt: National Security Agency
Sven Leyffer: Argonne National Laboratory
Todd Munson: Argonne National Laboratory

Computational Optimization and Applications, 2025, vol. 90, issue 2, No 1, 337-360

Abstract: Abstract We study the design of an electromagnetic cloak from multiple materials with an additional constraint on the mass of the cloak. Our problem is an example of a topology optimization problem, and we formulate this problem as a mixed-integer partial-differential equation constrained optimization (MIPDECO) problem, where Maxwell’s equation models the propagation of the wave through the cloak and surrounding medium. We use binary variables to model the assignment of the different materials, and their relevant properties (permittivity and density). The mass constraint adds a nontrivial constraint to this problem. We propose a two-phase strategy to solve this problem. In the first phase, we solve a continuous relaxation, and then propose a new variant of the feasibility pump that exploits the structure of the PDE to obtain an initial integral solution candidate. In the second phase, we use a trust-region approach to improve this incumbent. We also consider a continuation or mesh-sequencing approach to find better solutions faster on consecutively finer meshes. We present detailed numerical results to illustrate the effectiveness of our approaches for constructing multi-material cloaks with a mass constraint.

Keywords: Topology optimization; PDE-constrained optimization; Mixed-integer programming; Nonlinear optimization; 35J05; 49M37; 90C30 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10589-024-00644-x

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