383 citations · 1.2k across the 29 of their papers we have counts for
11 papers · 1 filter
An Empirical Quantile Estimation Approach to Nonlinear Optimization Problems with Chance Constraints
Fengqiao Luo, Jeffrey Larson
We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance const…
Structure-Aware Methods for Expensive Derivative-Free Nonsmooth Composite Optimization
Jeffrey Larson, Matt Menickelly
We present new methods for solving a broad class of bound-constrained nonsmooth composite minimization problems. These methods are specially designed for objectives that are some k…
Modeling Approaches for Addressing Simple Unrelaxable Constraints with Unconstrained Optimization Methods
Misha Padidar, Jeffrey Larson, Stefan M. Wild
We explore novel approaches for solving nonlinear optimization problems with unrelaxable bound constraints, which must be satisfied before the objective function can be evaluated.…
Derivative-Free Optimization of a Rapid-Cycling Synchrotron
Jeffrey S. Eldred, Jeffrey Larson, Misha Padidar +2
We develop and solve a constrained optimization model to identify an integrable optics rapid-cycling synchrotron lattice design that performs well in several capacities. Our model…
Multistart Algorithm for Identifying All Optima of Nonconvex Stochastic Functions
Prateek Jaiswal, Jeffrey Larson
We propose a multistart algorithm to identify all local minima of a constrained, nonconvex stochastic optimization problem. The algorithm uniformly samples points in the domain and…
Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions
Jeffrey Larson, Matt Menickelly, Baoyu Zhou
We propose a manifold sampling algorithm for minimizing a nonsmooth composition , where we assume is nonsmooth and may be inexpensively computed in closed form and…
Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints
Christian Kirches, Jeffrey Larson, Sven Leyffer +1
We propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a li…
Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization
S. Ashwin Renganathan, Jeffrey Larson, Stefan Wild
We propose a novel Bayesian method to solve the maximization of a time-dependent expensive-to-evaluate oracle. We are interested in the decision that maximizes the oracle at a fini…
A Repeated Route-then-Schedule Approach to Coordinated Vehicle Platooning: Algorithms, Valid Inequalities and Computation
Fengqiao Luo, Jeffrey Larson
Platooning of vehicles is a promising approach for reducing fuel consumption, increasing vehicle safety, and using road space more efficiently. We consider the important but diffic…
Derivative-free optimization methods
Jeffrey Larson, Matt Menickelly, Stefan M. Wild
In many optimization problems arising from scientific, engineering and artificial intelligence applications, objective and constraint functions are available only as the output of…
A Method for Convex Black-Box Integer Global Optimization
Jeffrey Larson, Sven Leyffer, Prashant Palkar +1
We study the problem of minimizing a convex function on a nonempty, finite subset of the integer lattice when the function cannot be evaluated at noninteger points. We propose a ne…