We present a new method to compute upper bounds of the number of solutions of binary integer programming (BIP) problems. Given a BIP, we create a dynamic programming (DP) table for a redundant knapsack constraint which is obtained by surrogate relaxation. We then consider a Lagrangian relaxation of the original problem to obtain an initial weight bound on the knapsack. This bound is then refine...

The dynamic stall phenomenon is characterized by the formation of a leading-edge vortex, which responsible for adverse aerodynamic forces and moments adversely impacting structural strength life system. Aerodynamic shape optimization (ASO) provides cost-effective approach to delay or mitigate characteristics. Unfortunately, ASO requires multiple evaluations accurate but time-consuming computati...

Starting from the defined network topology and the timetable assigned beforehand, the paper considers a train rescheduling in respond to disturbances that have occurred. Assuming that the train trips are jobs, which require the elements of infrastructure – resources, it was done by the mapping of the initial problem into a special case of job shop scheduling problem. In order to solve the given...

We present a new algorithm for penalized-likelihood emission image reconstruction. The algorithm monotonically increases the objective function, converges globally to the unique maximizer, and easily accommodates the nonnegativity constraint and nonquadratic but convex penalty functions. The algorithm is based on finding paraboloidal surrogate functions for the log-likelihood at each iteration:...

Injuries to the lower extremities are one of the major issues in vehicle to pedestrian collisions. To minimize injury risks of pedestrian lower extremity, this paper presents the design optimization of a typical vehicle front-end structure subjected to two different impact cases of TRL-PLI and Flex-PLI. Several approaches involving sampling techniques, surrogate model, multiobjective optimizati...

1 Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for prediction of spatiotemporally evolving flow dynamics Yu-Hung Chang a,*, Liwei Zhang a,**, Xingjian Wang a,†, Shiang-Ting Yeh a,††, Simon Mak b,‡, Chih-Li Sung b,‡, C. F. Jeff Wu b, §, Vigor Yang a, ¶ a School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA b School of Industrial and ...

Constrained reinforcement learning (CRL), also termed as safe learning, is a promising technique enabling the deployment of RL agent in real-world systems. In this paper, we propose successive convex approximation based off-policy optimization (SCAOPO) algorithm to solve general CRL problem, which formulated constrained Markov decision process (CMDP) context average cost. The SCAOPO on solving ...

Surrogates which allow one to predict the effect of the treatment on the outcome of interest from the effect of the treatment on the surrogate are of importance when it is difficult or expensive to measure the primary outcome. Unfortunately, the use of such surrogates can give rise to paradoxical situations in which the effect of the treatment on the surrogate is positive, the surrogate and out...

In this work we consider the task of constructing prediction intervals in an inductive batch setting. We present a discriminative learning framework which optimizes the expected error rate under a budget constraint on the interval sizes. Most current methods for constructing prediction intervals offer guarantees for a single new test point. Applying these methods to multiple test points results...