Engineering knowledge-based variance-reduction simulation and G-dominance for structural frame robust optimization

[EN] This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variance reduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables.The simultaneous minimization of the constrained weight (adding structuralweight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including

On reproduction in red algae: futher research needed at the molecular level

[EN]Multicellular red algae (Rhodophyta) have some of the most complex life cycles known in living organisms. Economically valuable seaweeds, such as phycocolloid producers, have a triphasic (gametophyte, carposporophyte, and tetrasporophyte) life cycle, not to mention the intricate alternation of generations in the edible “sushi-alga” nori. It is a well-known fact that reproductive processes are controlled by one or more abiotic factor(s), including day length, light quality, temperature, and nutrients. Likewise, endogenous chemical factors such as plant growth regulators have been reported to affect reproductive events in some red seaweeds. Still, in the genomic era and given the high throughput techniques at our disposal, our knowledge about the endogenous molecular machinery lags far behind that of higher plants.