Multi-Resolution Rendering for Computationally Expensive Lighting Effects

Memetic algorithm using multi-surrogates for computationally expensive optimization problems

In this paper, we present a Multi-Surrogates Assisted Memetic Algorithm (MSAMA) for solving optimization problems with computationally expensive fitness functions. The essential backbone of our framework is an evolutionary algorithm coupled with a local search solver that employs multi-surrogates in the spirit of Lamarckian learning. Inspired by the notion of 'blessing and curse of uncertainty'...

Eecient Linear Re-rendering for Interactive Lighting Design Eecient Linear Re-rendering for Interactive Lighting Design

We present a framework for interactive lighting design based on linear re-rendering. The rendering operation is linear with respect to light sources, assuming a xed scene and camera geometry. This linearity means that a scene may be interactively re-rendered via linear combination of a set of basis images, each rendered under a particular basis light. We focus on choosing and designing a suitab...

Sequential Domain Patching for Computationally Feasible Multi-objective Optimization of Expensive Electromagnetic Simulation Models

Vast majority of practical engineering design problems require simultaneous handling of several criteria. For the sake of simplicity and through a priori preference articulation one can turn many design tasks into single-objective problems that can be handled using conventional numerical optimization routines. However, in some situations, acquiring comprehensive knowledge about the system at ha...

A multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems

Integrating data-driven surrogate models and simulation models of di erent accuracies (or delities) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple delities in global optimization is a major challenge. To address it, the two major contrib...

Multiple Objective Evolutionary Algorithms for Independent, Computationally Expensive Objective Evaluations