Multiobjective engineering design optimization problems: a sensitivity analysis approach

This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper.

Cone photopigment variations in Cebus apella monkeys evidenced by electroretinogram measurements and genetic analysis

We investigated the color vision pattern in Cebus apella monkeys by means of electroretinogram measurements (ERG) and genetic analysis. Based on ERG we could discriminate among three types of dichromatic males. Among females, this classification is more complex and requires additional genetic analysis. We found five among 10 possible different phenotypes, two trichromats and three dichromats. We also found that Cebus present a new allele with spectral peak near 552 nm, with the amino acid combination SFT at positions 180, 277 and 285 of the opsin gene, in addition to the previously described SYT, AFT and AFA alleles. (C) 2009 Elsevier Ltd. All rights reserved.