An outer-approximation algorithm for generalized maximum entropy sampling

Han-Lim Choi, Jonathan P. How, Paul I. Barton
2008 2008 American Control Conference  
This paper presents an outer-approximation algorithm to address a generalized maximum entropy sampling (GMES) problem that determines a set of measurement locations providing the largest entropy reduction. A new mixedinteger semidefinite program (MISDP) formulation is proposed to handle a GMES problem with a jointly Gaussian distribution over the search space. This formulation employs binary variables to indicate if the corresponding measurement location is selected, and exploits the linear
more » ... valent form of a bilinear term involving binary variables to ensure convexity of the objective function and linearity of the constraint functions. An outerapproximation algorithm is developed for this formulation that obtains the optimal solution by solving a sequence of mixedinteger linear programs. Numerical experiments are presented to verify the solution optimality and the computational effectiveness of the proposed algorithm by comparing it with an existing branch-and-bound method that utilizes nonlinear programming relaxation. Sensor selection for best tracking of a moving target under a communication budget constraint is specifically considered to validate the superiority of the suggested algorithm in handling quadratic constraints.
doi:10.1109/acc.2008.4586756 dblp:conf/amcc/ChoiHB08 fatcat:y4nycpkjhbe7xlihj754ilwzhe