Search results
1 – 10 of over 10000In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers…
Abstract
Purpose
In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers to the essence of real-life engineering systems and complex natural mechanisms which are generally multi-modal, non-convex and multi-criterion. Until now, several deterministic and stochastic methods have been proposed to cope with such complex systems. Advanced soft computational methods such as evolutionary games (cooperative and non-cooperative), Pareto-based techniques, fuzzy evolutionary methods, cooperative bio-inspired algorithms and neuro-evolutionary systems have effectively come to the aid of researchers to build up efficient paradigms with application to vector optimization. The paper aims to discuss this issue.
Design/methodology/approach
A novel hybrid algorithm called synchronous self-learning Pareto strategy (SSLPS) is presented for the sake of vector optimization. The method is the ensemble of evolutionary algorithms (EA), swarm intelligence (SI), adaptive version of self-organizing map (CSOM) and a data shuffling mechanism. EA are powerful numerical optimization algorithms capable of finding a global extreme point over a wide exploration domain. SI techniques (the swarm of bees in our case) can improve both intensification and robustness of exploration. CSOM network is an unsupervised learning methodology which learns the characteristics of non-dominated solutions and, thus, enhances the quality of the Pareto front.
Findings
To prove the effectiveness of the proposed method, the authors engage a set of well-known benchmark functions and some well-known rival optimization methods. Additionally, SSLPS is employed for optimal design of shape memory alloy actuator as a nonlinear multi-modal real-world engineering problem. The experiments show the acceptable potential of SSLPS for handling both numerical and engineering multi-objective problems.
Originality/value
To the author’s best knowledge, the proposed algorithm is among the rare multi-objective methods which fosters the use of automated unsupervised learning for increasing the intensity of Pareto front (while preserving the diversity). Also, the research evaluates the power of hybridization of SI and EA for efficient search.
Details
Keywords
The purpose of this paper is to define the process of analog circuit optimization on the basis of the control theory application. This approach produces many different strategies…
Abstract
Purpose
The purpose of this paper is to define the process of analog circuit optimization on the basis of the control theory application. This approach produces many different strategies of optimization and determines the problem of searching of the best strategy in sense of minimal computer time. The determining of the best strategy of optimization and a searching of possible structure of this strategy with a minimal computer time is a principal aim of this work.
Design/methodology/approach
Different kinds of strategies for circuit optimization have been evaluated from the point of view of operations’ number. The generalized methodology for the optimization of analog circuit was formulated by means of the optimum control theory. The main equations for this methodology were elaborated. These equations include the special control functions that are introduced artificially. This approach generalizes the problem and generates an infinite number of different strategies of optimization. A problem of construction of the best algorithm of optimization is defined as a typical problem of the control theory. Numerical results show the possibility of application of this approach for optimization of electronic circuits and demonstrate the efficiency and perspective of the proposed methodology.
Findings
Examples show that the better optimization strategies that are appeared in limits of developed approach have a significant time gain with respect to the traditional strategy. The time gain increases when the size and the complexity of the optimized circuit are increasing. An additional acceleration effect was used to improve the properties of presented optimization process.
Originality/value
The obtained results show the perspectives of new approach for circuit optimization. A large set of various strategies of circuit optimization serves as a basis for searching the better strategies with a minimum computer time. The gain in processor time for the best strategy reaches till several thousands in comparison with traditional approach.
Details
Keywords
Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed…
Abstract
Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed performance. Notes that 18 papers from the Symposium are grouped in the area of automated optimal design. Describes the main challenges that condition computational electromagnetism’s future development. Concludes by itemizing the range of applications from small activators to optimization of induction heating systems in this third chapter.
Details
Keywords
Yuliya Pleshivtseva, Edgar Rapoport, Bernard Nacke, Alexander Nikanorov, Paolo Di Barba, Michele Forzan, Elisabetta Sieni and Sergio Lupi
This paper aims to investigate different multi-objective optimization (MOO) approaches for design and control of electromagnetic devices. The main goal of MOO is to find the set…
Abstract
Purpose
This paper aims to investigate different multi-objective optimization (MOO) approaches for design and control of electromagnetic devices. The main goal of MOO is to find the set of design variables or control parameters which will provide the best possible values of typical conflicting objective functions.
Design/methodology/approach
In the research studies, standard genetic algorithm (GA), non-dominated sorting GA (NSGA-II), migration NSGA algorithm and alternance method of optimal control theory are discussed and compared.
Findings
The test practical problems of multi-criteria optimization of induction heating processes with respect to chosen quality criteria confirm the effectiveness of application of considered MOO approaches both for the problems of design and control.
Originality/value
This paper represents and investigates different MOO approaches for design and control of electrotechnological systems.
Details
Keywords
Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the…
Abstract
Purpose
Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the amount of deteriorate at any time, this paper aims to present a prognostics approach based on integrating optimize health indicator (OHI) and machine learning algorithm.
Design/methodology/approach
Proposed optimum prediction model would be used to evaluate the remaining useful life (RUL) of REBs. Initially, signal raw data are preprocessing through mother wavelet transform; after that, the primary fault features are extracted. Further, these features process to elevate the clarity of features using the random forest algorithm. Based on variable importance of features, the best representation of fault features is selected. Optimize the selected feature by adjusting weight vector using optimization techniques such as genetic algorithm (GA), sequential quadratic optimization (SQO) and multiobjective optimization (MOO). New OHIs are determined and apply to train the network. Finally, optimum predictive models are developed by integrating OHI and artificial neural network (ANN), K-mean clustering (KMC) (i.e. OHI–GA–ANN, OHI–SQO–ANN, OHI–MOO–ANN, OHI–GA–KMC, OHI–SQO–KMC and OHI–MOO–KMC).
Findings
Optimum prediction models performance are recorded and compared with the actual value. Finally, based on error term values best optimum prediction model is proposed for evaluation of RUL of REBs.
Originality/value
Proposed OHI–GA–KMC model is compared in terms of error values with previously published work. RUL predicted by OHI–GA–KMC model is smaller, giving the advantage of this method.
Details
Keywords
I. Scott, A. Vukovic and P. Sewell
The purpose of this paper is to report on the use of conjugate‐gradients (CG) as a means to accelerate the convergence of the iterative time‐reversal algorithm used for…
Abstract
Purpose
The purpose of this paper is to report on the use of conjugate‐gradients (CG) as a means to accelerate the convergence of the iterative time‐reversal algorithm used for optimisation of electromagnetic devices.
Design/methodology/approach
The numerical time‐domain transmission line modelling method is used for time‐reversal optimisation. A comparison of the standard and CG time‐reversal is shown for two examples of microwave bandpass filter optimisation.
Findings
The paper demonstrates the time‐reversal optimisation that uses the CG matrix solver for perturbing the time reversal mirrors (TRM) fields.
Originality/value
The paper outlines the perturbation procedure of the CG time‐reversal and compares it to the standard time‐reversal optimisation. Two examples of microwave band pass filter optimisation have been considered and in each case it was demonstrated that CG time‐reversal significantly accelerates the optimisation process compared to the standard time‐reversal simulations.
Details
Keywords
The purpose of this paper is to propose a solution of the engine bypass ratio choice problem of a very light jet (VLJ) class aircraft using the multiple objective optimization…
Abstract
Purpose
The purpose of this paper is to propose a solution of the engine bypass ratio choice problem of a very light jet (VLJ) class aircraft using the multiple objective optimization (MOO) method.
Design/methodology/approach
The work focuses on the choice of one of the most essential parameters of the jet engine, that is its bypass ratio. The work presents the methodology of optimal designing using the multitask character of the matter which is based on the mathematical model of optimization in the concept of the set theory. To make an optimal choice of the chosen parameter, a complete computational model of an aircraftwas made (aerodynamic, power unit, performance and cost) and then the method that allows to choose the bypass ratio was selected, regardingmultiple estimating criteria of the obtained solutions. The presented method can be used at the concept design state for determining the chosen and most important technical parameters of the aircraft.
Findings
The way to design a competing aircraft is to choose its design parameters, including the power unit, by using the advanced methods of MOO. The main aim of the work was to demonstrate a method of selecting chosen parameters of the transport aircraft at the preliminary design stage. The work focuses on the choice of bypass ratio of the jet engine of the VLJ. The method could be helpful at the preliminary design stage of a new aircraft to selection of other design parameters.
Research limitations/implications
The exemplary calculations were made for 50 different transport tasks to take into account different performance conditions of the aircraft. The presented method can be used at the concept design state for determining the chosen and most important technical parameters of the aircraft.
Practical implications
The work shows a practical possibility to implement the proposed method. The presented method could be helpful at the preliminary design stage of a new aircraft to select its design parameters. The results of the analyses are a separate point for further research and studies.
Originality/value
The work shows a practical possibility to implement the proposed approach for design problems at early stages of product development.
Details
Keywords
Anand Amrit, Leifur Leifsson and Slawomir Koziel
This paper aims to investigates several design strategies to solve multi-objective aerodynamic optimization problems using high-fidelity simulations. The purpose is to find…
Abstract
Purpose
This paper aims to investigates several design strategies to solve multi-objective aerodynamic optimization problems using high-fidelity simulations. The purpose is to find strategies which reduce the overall optimization time while still maintaining accuracy at the high-fidelity level.
Design/methodology/approach
Design strategies are proposed that use an algorithmic framework composed of search space reduction, fast surrogate models constructed using a combination of physics-based surrogates and kriging and global refinement of the Pareto front with co-kriging. The strategies either search the full or reduced design space with a low-fidelity model or a physics-based surrogate.
Findings
Numerical investigations of airfoil shapes in two-dimensional transonic flow are used to characterize and compare the strategies. The results show that searching a reduced design space produces the same Pareto front as when searching the full space. Moreover, as the reduced space is two orders of magnitude smaller (volume-wise), the number of required samples to setup the surrogates can be reduced by an order of magnitude. Consequently, the computational time is reduced from over three days to less than half a day.
Originality/value
The proposed design strategies are novel and holistic. The strategies render multi-objective design of aerodynamic surfaces using high-fidelity simulation data in moderately sized search spaces computationally tractable.
Details
Keywords
Ghaith Warkozek, Stéphane Ploix, Frédéric Wurtz, Mireille Jacomino and Benoit Delinchant
The purpose of this paper is to introduce a problematic phenomenon that can occur when managing multi electrical sources systems by optimization.
Abstract
Purpose
The purpose of this paper is to introduce a problematic phenomenon that can occur when managing multi electrical sources systems by optimization.
Design/methodology/approach
The energy management problem is formulated as a linear optimisation problem. Two approaches are developed and applied to detect the possible existence of equivalents solutions. The first is based on Dulmage‐Mendelsohn (DM) decomposition. With this method the structure of the optimisation problem is analysed. The second approach is a numeric approach; the detection of equivalents solutions is made by the formulation of new optimisation problem and the objective function of this problem is to maximise the distance between two equivalents solutions.
Findings
The numeric approach is more efficient than the structural approach. In some cases, applying DM decomposition may not be sufficient to detect the risk of W effect. This is because DM decomposition does not take the value of variable's coefficient into consideration, which is important to determine the degrees of freedom in the set of variables.
Originality/value
Multi sources systems are widely used, especially in buildings where renewable energies have good potential application. The linear formulation of the management problem may induce an existence of equivalent command strategies. The detection approach presented in this paper shows that some solutions are better than others from an applicabability point of view. They will not exhaust rapidly the storage system. This approach can be implemented in virtual sources plant to avoid solutions with this so‐called W effect.
Details
Keywords
A survey of multi-objective scheduling techniques on the job shop problem is offered in this chapter. The survey traces the development of techniques from Integer programming to…
Abstract
A survey of multi-objective scheduling techniques on the job shop problem is offered in this chapter. The survey traces the development of techniques from Integer programming to genetic algorithms that take advantage of the power of recent computing technology. Applications are in areas as diverse as job scheduling, nurse scheduling, and groundwater monitoring.