Impacts of problem scale and sampling strategy on surrogate model accuracy: An application of surrogate-based optimization in building design

Surrogate-based Optimization is a useful approach when the objective function is computationally expensive to evaluate, compared to Simulation-based Optimization. In the surrogate-based method, analytically tractable “surrogate models” (also known as “Response Surface Models — RSMs” or “metamodels”), are constructed and validated for each...

A cognitive system based on fuzzy information processing and multi-objective evolutionary algorithm

A cognitive system is presented, which is based on coupling a multi-objective evolutionary algorithm with a fuzzy information processing system. The aim of the system is to identify optimal solutions for multiple criteria that involve linguistic concepts, and to systematically identify a most suitable solution among the alternatives. The...

Multi-objective optimization in the construction industry

Multi-objective-optimization-based positioning of houses in a residential neighborhood is described. The task is the placement of the buildings in a favorable configuration constrained by two objectives, which are garden performance and visual privacy performance requirements. The method used is evolutionary computation with the Pareto front...