[PDF] Top 20 Optimal Thermodynamic Design of Turbofan Engines using Multi-objective Genetic Algorithm

... NSGA algorithm led to the modified version of NSGA- II [18] in which the sharing method has been replaced by a direct elitist method in order to preserve the population ...modified algorithm is the ... See full document

... novel optimal approach of control strategy is introduced by applying fractional calculus in the structure of sliding mode control for a range of dynamics system liable to ...a multi-objective ... See full document

... between objective functions, and select the suitable design point through all optimal ...weight objective functions which are impossible to obtain using single- objective ... See full document

... (2008) design a performance approximation method for pick-and-pass warehouse system based on queuing network ...use genetic algorithm (GA) to optimize item allocation with reducing travel time of ... See full document

... paper, optimal multi-objective Pareto design of robust state feedback controllers for an inverted pendulum with parameters probabilistic uncertainty is ...The objective functions that ... See full document

... solve multi-variant ...EWR. Genetic algorithms (GA) and artificial neural networks (ANN) are popular software technologies used for the optimization of machining ...by using back-propagation neural ... See full document

... the optimal parameter values was performed using Matlab program assistance, namely multi-objective (multi-objective optimization using Genetic ...a multi- ... See full document

... as design variable : sizing configuration and topological ...the design variables and the coordinates of the nodes and the connectivity between various members are ...the design variables are the ... See full document

... an objective function (also call cost function) and the GA will evaluate the objective function for given input parameters (Neeraj and Kumar, ...the genetic algorithm is applied for ... See full document

... useful optimal design principles involved the performance of turboprop can be discovered by the pareto-based two- objective ...important optimal principles would not be obtained without the ... See full document

... As can be seen at Figure 1, there are two objective(s), which is to minimize both cost function (y (1)) and time (y (2)). In this optimization process, decision variables indicated by worker’s working hours that ... See full document

... of Multi-objective EAs (MOEAs) in the query definition problem has been proved as advantageous; due to MOEAs can learn a set of queries with good precision recall trade- off in a unique ... See full document

... The formation of dynamic cell manufacturing is one of the hottest topics in the field of advance production operations. This text discusses the problem of the formation of dynamic cell. Through trade-off between 3 ... See full document

... provide flexibility and to exert force. Helical springs are most popular type of springs. The method of helical spring optimization is a typical one which can be used to solve mechanical optimum design problem. An ... See full document

... The objective is to determine a set of model parameters, such that model simulations using these parameters simultaneously fit all the above three sets of experimental data with minimum ...Present ... See full document

... is optimal and one which is non optimal. Although a two-objective problem is illustrated ...of optimal solutions contains more than one ...Pareto optimal solutions denoted by ...Pareto ... See full document

... The TEP algorithm was applied to the 6–machine 8–bus test system shown in Fig. 6. Network data for this system can be found in [19–20] and other data are given in the Appendix. The 6–machine 8–bus system consists ... See full document

... Popov, A., Farag, A. and Werner, H. (2005). Tuning of a PID controller using a multi-objective optimization technique applied to a neutralization plant. In: Decision and Control, 2005 and 2005 ... See full document

... Searching invisible information and pattern from large database is the work of data mining. High dimensionality is become a curse for data mining which generates problem while training the data. The curse of ... See full document

... Apriori Algorithm plays an important role in deriving frequent itemsets and then extracting association rules out of ...Apriori Algorithm uses Conjunctive nature of association rules, and single minimum ... See full document