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A robust optimization algorithm integrating Kriging models and nested GA is proposed to directly solve the constrained interval robust optimization model of the uncertain structure.
To overcome these shortcomings, a novel optimization algorithm is proposed for directly solving the nonlinear constrained interval optimization models based on a novel concept of the degree of interval constraint violation (DICV) and the DICV-based preferential guidelines.
A constrained interval optimization model is proposed for the optimization of uncertain structures with their mechanical performance indices described as the objective and constraint functions of the design vector and interval uncertain parameters.
The constrained interval robust optimization model in Eq. (13) is also solved by our previous algorithm [27] with the GA parameters and convergent threshold settled the same as those in the proposed algorithm.
Then the robustness based preferential guidelines were proposed for directly ranking various design vectors and an algorithm integrating Kriging technique and nested GA was put forward to realize the direct solution of the constrained interval robust optimization problem.
The constrained interval robust optimization model in Eq. (12) is utilized as a benchmark example, which is firstly solved by the proposed algorithm with the GA parameters listed in Table 1.
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The only difference is that Alta is also a price bidder of the whole bidding process at this time with bidding strategic coefficient constrained in interval [1, 5] such that the wind unit's bid can be up to 35 $/MWh, which is in a comparable range of the bids of the other strategic units.
In choosing the sample size, we balanced the burden of manual classification by the clinicians and the need for reasonably constrained confidence intervals.
Although we cannot currently determine exactly when the Central American Peninsula formed or how far east it may have extended, we can constrain the interval of time that such a peninsula may have existed by placing the land mammals of the Cucaracha Formation into a well-defined stratigraphy.
The end-Triassic mass extinction interval in the studied section is well constrained within the interval of a chert bed number 796 based on the radiolarian faunal turnover from the Globolaxtorum tozeri zone to Pantanellium tanuense zone with the last occurrence of conodont Misikella posthernsteini (Hori, 1992; Carter and Hori, 2005).
Fitting the model with τ constrained to an interval typically yields a τ value at either endpoint, reflecting the constraint, except for those intervals which contain τ values at which the Deviance attains a local minimum.
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