1 citations · 1 across the 4 of their papers we have counts for
5 papers
Dimensional Peeking for Low-Variance Gradients in Zeroth-Order Discrete Optimization via Simulation
Philipp Andelfinger, Wentong Cai
Gradient-based optimization methods are commonly used to identify local optima in high-dimensional spaces. When derivatives cannot be evaluated directly, stochastic estimators can…
Learning to Optimize Capacity Planning in Semiconductor Manufacturing
Philipp Andelfinger, Jieyi Bi, Qiuyu Zhu +7
In manufacturing, capacity planning is the process of allocating production resources in accordance with variable demand. The current industry practice in semiconductor manufacturi…
Differentiable Agent-Based Simulation for Gradient-Guided Simulation-Based Optimization
Philipp Andelfinger
Simulation-based optimization using agent-based models is typically carried out under the assumption that the gradient describing the sensitivity of the simulation output to the in…
A Survey on Agent-based Simulation using Hardware Accelerators
Jiajian Xiao, Philipp Andelfinger, David Eckhoff +2
Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulat…
Enabling Cross-Event Optimization in Discrete-Event Simulation Through Compile-Time Event Batching
Marc Leinweber, Hannes Hartenstein, Philipp Andelfinger
A discrete-event simulation (DES) involves the execution of a sequence of event handlers dynamically scheduled at runtime. As a consequence, a priori knowledge of the control flow…