Multicriteria analysis of real-life engineering optimization problems: statement and solution

The article of record as published may be located at http://dx.doi.org/10.1016/j.na.2005.01.028The majority of engineering problems are essentially multicriteria. These criteria are usually contradictory. That is why specialists experience significant difficulties in correctly stating engineering optimization problems, so designers often end up solving ill-posed problems. In general, it is impossible to reduce multicriteria problems to single-criterion ones. For the correct statement and solution of engineering optimization problems, a method called Parameter Space Investigation (PSI method) has been created and widely integrated into various fields of industry, science, and technology (e.g., design of the space shuttle, nuclear reactor, missile, automobile, ship, and metal-tool). In summary, the PSI method generates many feasible designs from which the so-called Pareto optimal ones (i.e. solutions which cannot be improved) are extracted. The PSI method can also be used to efficiently optimize models in a parallel mode, which is of great importance while solving high-dimensional multiparameter and multicriteria problems. The PSI method is implemented in the software package Multicriteria Optimization and Vector Identification (MOVI), a comprehensive system for multicriteria engineering optimization (design, identification, and control). This system allows optimization of many problems that until recently appeared intractable

Multicriteria Parametrical Identification of the Parafoil-Load Delivery System

18th AIAA Aerodynamic Decelerator Systems Technology Conference and Seminar, Munich, Germany, May 23-26, 2005.This paper addresses the problem of multicriteria (versus single-criterion) parametrical identification of the autonomously controlled cargo parafoil. Based on the structural identification as an initial step toward creation of an adequate model of the parafoil, a high-fidelity model including several dozens of optimization parameters has been developed. The present paper proposes the correct statement of the multicriteria parametrical identification problem including the necessity to investigate the feasible set of variable parameters. The paper advocates the use of the Parameter Space Investigation method and Multicriteria Optimization / Vector Identification software package to solve the problem

Learning about occlusion : Initial assumptions and rapid adjustments

We examined 6-month-olds abilities to represent occluded objects, using a corneal-reflectioneye-tracking technique. Experiment 1 compared infants’ ability to extrapolate the currentpre-occlusion trajectory with their ability to base predictions on recent experiences of novelobject motions. In the first condition infants performed at asymptote (≈2/3 accurate predictions)from the first occlusion passage. In the second condition all infants initially failed tomake accurate prediction. Performance, however, reached asymptote after two occlusion passages.This is the first study that demonstrates such rapid learning effects during an occlusiontask. Experiment 2 replicates these effects and demonstrates a robust memory effect extending24 h. In occlusion tasks such long-term memory effects have previously only been observed in14-month-olds (Moore & Meltzoff, 2004)