Product evolutionary design driven by environmental performance

This article is in terms of product environmental performance demand and proposes four structure evolutionary operation modes which include combined evolutionary method, decomposition evolutionary method, replacement evolutionary method, and material-changing evolutionary method to express the structure evolutionary process of products. Through the quotient space theory and proposed method combined with probability statistics, probability mapping from environmental performance to product structure is established and the evolutionary individuals with outstanding environmental performance are listed. Through the analysis to the specific conditions of the evolutionary individuals, the design constraints are extracted, and the objective function of environmental performance is established. This article presents an interactive genetic algorithm as evolutionary algorithm and combines it with four structure evolutionary operation modes to conduct corresponding gene manipulation and generates evolutionary product. Finally, the proposed methodology is successfully applied to engine gear chamber and the environmental impact is found to be better than before evolution.

Uncertainty about future payoffs makes impatience rational

Uncertainty (i.e., variable payoffs with unknown probabilities) brings together a number of features of the authors' argument. It leads to present bias, even for completely rational agents with time-consistent preferences. As an evolutionary product of Pleistocene climate instability, humans possess broad adaptations to environmental uncertainty, giving rise to key features of the behavioral constellation of deprivation (BCD).