This study proposed a new method of multiobjectiveoptimization. Present multiobjectiveoptimization produces only a single solution set. This is a major limitation of the present multiobjectiveoptimization technique...
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This paper proposes an improvement of an efficient multiobjectiveoptimization algorithm, Non-dominated Sorting Genetic Algorithm II, NSGA-II, that has been here applied to solve the problem of optimal capacitors plac...
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This paper proposes an improvement of an efficient multiobjectiveoptimization algorithm, Non-dominated Sorting Genetic Algorithm II, NSGA-II, that has been here applied to solve the problem of optimal capacitors placement in distribution systems. The studied improvement involves the Crowded Comparison Operator and modifies it in order to handle several constraints. The problem of optimal location and sizing of capacitor banks for losses reduction and voltage profile flattening in medium voltage (MV) automated distribution systems is a difficult combinatorial constrainedoptimization problem which is deeply studied in literature. In this paper, the efficiency of the proposed Crowded Comparison Operator, CCO1, is compared to the efficiency of another Crowded Comparison Operator, CCO2, whose definition derives from the constraint-domination principle proposed by Deb et al. The two operators are tested on difficult test problems as well as on the optimal capacitors placement problem. (c) 2006 Elsevier Ltd. All rights reserved.
This paper proposes a new multiobjectiveoptimization with elliptical constraints approach for nonlinear models implemented in a cladding process of ABNT 1020 carbon steel plate using austenitic ABNT 316L stainless st...
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This paper proposes a new multiobjectiveoptimization with elliptical constraints approach for nonlinear models implemented in a cladding process of ABNT 1020 carbon steel plate using austenitic ABNT 316L stainless steel cored wire. Stainless steel stands out among the cladding materials as it allows obtaining surfaces with determined desirable characteristics from lower cost materials. This kind of process may be controlled by a relatively small number of input variables, i.e., the wire feed rate (WF), voltage (V), welding speed (WS), and the distance from the contact tip to the workpiece (N). Besides that, many outputs can be evaluated and simultaneously optimized. In the present paper, dilution (D), yield (Y), convexity index (CI), and penetration index (PI) were investigated. In order to consider the problem's multivariate nature, techniques such as factor analysis and Bonferroni's multivariate intervals were applied combined with elliptical constraints. The response variables were mathematically modeled using Poisson regression, and the obtained results were satisfactory since accurate models were achieved. The normal boundary intersection (NBI) method produced a set of viable configurations for the input variables that allows the experimenter to encounter the best system setup regarding the importance level of each response. Feasible and non-dominated solutions were found which means that the best possible scenario considering all the constraints was reached.
The welding process in aluminum is a complex process that commonly presents several issues such as weld bead discontinuity, cracks, and lack of penetration. Thus, an accurate specification of the parameters in order t...
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The welding process in aluminum is a complex process that commonly presents several issues such as weld bead discontinuity, cracks, and lack of penetration. Thus, an accurate specification of the parameters in order to achieve optimal values for the investigated responses is aimed by the industry. The present paper proposes the application of a multiobjectiveoptimization approach considering multivariate constraints based on the simultaneous confidence intervals and the elliptical region of the correlated data. Structured experiments for the welding process of aluminum alloy (AA) 6063 TA tubes used in corona rings were performed according to a face-centered composite design with 4 factors, wire feed rate (Wf), arc voltage (V), contact tip to the workpiece distance (Ct), and motor frequency (Fr), resulting in 31 experiments. Poisson regression was applied to model the values of yield (Y), dilution (D), reinforcement index (RI), and penetration index (PI), allowing to estimate the optimal individual values with regard to the multivariate constraints. Rotated factor scores were obtained in order to replace the original data, and therefore, the factor multivariate square error was used as objective functions to be minimized through normal boundary intersection method. A satisfactory weld bead with large values of PI, D, and Y and a small value of RI was reached as prespecified by the manager of the process.
This study extends a comprehensive closed-loop physiological model of the circulatory system based on lumped electrical analogue components. The model associates subject specific factors such as age, gender, body surf...
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ISBN:
(纸本)9781479943463
This study extends a comprehensive closed-loop physiological model of the circulatory system based on lumped electrical analogue components. The model associates subject specific factors such as age, gender, body surface area, fitness and smoking habits, with cardiovascular parameters including vascular blood pressures, blood volumes, and cardiac output, providing physiological insight via the interpretation of the model's parameters. The model parameters were determined using multi-objective constrainedoptimization in a typical inverse problem setup, and were subsequently associated with the subject specific factors using least squares polynomial relationships with l(1)-l(2)-norm regularization. We validated the performance of the model using data from 289 subjects, replicating arterial blood pressure accurately (about 4.8% relative deviation from the measured values), whilst also providing physiologically realistic estimates of vascular blood pressures, blood volumes, and cardiac output.
High-Altitude Pseudo-Satellites (HAPS) are long-endurance, fixed-wing, lightweight Unmanned Aerial Vehicles (UAVs) that operate in the stratosphere and offer a flexible alternative for ground activity monitoring/imagi...
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ISBN:
(纸本)9781450361118
High-Altitude Pseudo-Satellites (HAPS) are long-endurance, fixed-wing, lightweight Unmanned Aerial Vehicles (UAVs) that operate in the stratosphere and offer a flexible alternative for ground activity monitoring/imaging at specific time windows. As their missions must be planned ahead (to let them operate in controlled airspace), this paper presents a Genetic Algorithm (GA)-guided Hierarchical Task Network (HTN)-based planner for multiple HAPS. The HTN allows to compute plans that conform with airspace regulations and operation protocols. The GA copes with the exponentially growing complexity (with the number of monitoring locations and involved HAPS) of the combinatorial problem to search for an optimal task decomposition (that considers the time-dependent mission requirements and the time-varying environment). Besides, the GA offers a flexible way to handle the problem constraints and optimization criteria: the former encodes the airspace regulations, while the latter measures the client satisfaction, the operation efficiency and the normalized expected mission reward (that considers the wind effects in the uncertainty of the arrival-times at the monitoring-locations). Finally, by integrating the GA into the HTN planner, the new approach efficiently finds overall good task decompositions, leading to satisfactory task plans that can be executed reliably (even in tough environments), as the results in the paper show.
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