Self-adaptive NGSA algorithm and optimal design of inductors for magneto-fluid hyperthermia

2017 ◽  
Vol 36 (2) ◽  
pp. 535-545 ◽  
Author(s):  
Paolo Di Barba ◽  
Fabrizio Dughiero ◽  
Michele Forzan ◽  
Elisabetta Sieni
Keyword(s):  
Optimal Design ◽  
Optimization Algorithm ◽  
Design Methodology ◽  
Magnetic Nanoparticle ◽  
Petri Dish ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Content Type ◽  
Magnetic Fluid Hyperthermia ◽  
A Cell

Purpose This paper aims to present the optimal design of an inductor used to heat a magnetic nanoparticle fluid injected in a cell culture inside a Petri dish. Design/methodology/approach The inductor design is driven by means of a multi-objective optimization algorithm that generalizes the migration-non-dominated sorting genetic algorithm (NSGA); it is called self-adapting migration-NSGA. Findings The optimized device is able to synthesize a uniform magnetic field in a nanoparticle fluid, substantially helping its heating capability. The ultimate scope is to assist the cancer therapy based on magnetic fluid hyperthermia (MFH). Originality/value The optimal design of an inductor for MFH applications has been carried out by applying an improved version of migration-based NSGA-II algorithm including automatic stop and a self-adapting concept. The modified optimization algorithm is suitable to find better optimal solutions with respect to a standard version of NSGA-II.

Switching harmonic suppression design based on multi-objective optimization algorithm with constraint processing

2020 ◽  
Vol 39 (4) ◽  
pp. 899-913
Author(s):  
Songtao Huang ◽  
Jie Ye ◽  
Haozhe Wang ◽  
Baojin Li ◽  
Anwen Shen ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Filter Design ◽  
Design Parameters ◽  
Harmonic Suppression ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Filter Parameter ◽  
Content Type ◽  
Domain Experts ◽  
Multi Objective

Purpose Traditional switching harmonic suppressor design methods require domain experts to adjust design parameters due to various complex performance requirements and practical limitations in switching ripple suppressor designs. The purpose of this paper is to present a method for filter parameter design. Design/methodology/approach An improved non-dominated sorting genetic algorithm II (NSGA II) was used in the inductor-capacitor-inductor (LCL) filter design to find the optimal design parameters, and a method was proposed to handle the constraints by transforming the them into decision variables. Findings The performance of the proposed algorithm in parameter designing was verified by simulation on MATLAB and experimental results on hardware-in-the-loop plat-form with StarSim software. The results indicate that the optimization algorithm has a better effect than the traditional expert parameters on each optimization index, especially on the switching harmonic suppression. Originality/value The paper presents an improved multi-objective optimization algorithm with ingenious constraints handing to obtain better filter parameters and reduces switching harmonics.

Design and control of electrotechnological systems

2019 ◽  
Vol 39 (1) ◽  
pp. 239-247
Author(s):  
Yuliya Pleshivtseva ◽  
Edgar Rapoport ◽  
Bernard Nacke ◽  
Alexander Nikanorov ◽  
Paolo Di Barba ◽  
...  
Keyword(s):  
Design Methodology ◽  
Quality Criteria ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Content Type ◽  
Electromagnetic Devices ◽  
Design Variables ◽  
And Control ◽  
Standard Genetic Algorithm

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.

scholarly journals The next frontier: using space as management strategy - an exploratory study

2020 ◽  
Vol 33 (3) ◽  
pp. 217-229
Author(s):  
Pia Storvang ◽  
Bang Nguyen
Keyword(s):  
Management Strategy ◽  
Design Methodology ◽  
Physical Space ◽  
Organizational Strategy ◽  
University Campus ◽  
Content Type ◽  
Industrial Setting ◽  
Cell Organization ◽  
A Cell ◽  
The University

Purpose More and more companies use physical space as a way to enhance creativity, create change and stimulate interaction. The purpose of this paper is to investigate how space affects this interrelationship and explores how space can support organizational strategy. Design/methodology/approach Using a qualitative approach, this study explores three cases from an educational, a cultural and an industrial setting to illustrate how space can be used to support an organization’s policy and help its strategic intentions. Findings The findings demonstrate how space can be used to enhance organizational strategy and demonstrate how closely the creation of space can be related to the development of that strategy. Specifically, the study finds that the “’space-organizational strategy’ link has three uses: “Space as an organizational meeting place” in the University campus, (2) “Space as a network organization” in the culture and production center and (3) “Space as a cell organization” in the private manufacturing company. Originality/value The study will show that the design and operationalization of spaces can influence management and organizational strategy because space influences relations between people and that organizations can use space to support their strategic intentions seems to have been overlooked in the literature.

Shuffled shepherd optimization method: a new Meta-heuristic algorithm

2020 ◽  
Vol 37 (7) ◽  
pp. 2357-2389 ◽  
Author(s):  
Ali Kaveh ◽  
Ataollah Zaerreza
Keyword(s):  
Heuristic Algorithm ◽  
Optimization Algorithm ◽  
Design Methodology ◽  
Optimization Method ◽  
Optimization Process ◽  
Heuristic Optimization ◽  
Benchmark Problems ◽  
Content Type

Purpose This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm. Design/methodology/approach The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community. Findings A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples. Originality/value A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized.

Hybrid QPSO-NNIA2 Algorithm for Multi-Objective Optimization Problem

2019 ◽  
Vol 33 (08) ◽  
pp. 1959025
Author(s):  
Lan Zhang
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Nearest Neighbor ◽  
Superior Performance ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Evolution Algebra ◽  
Neighbor List

To improve the convergence and distribution of a multi-objective optimization algorithm, a hybrid multi-objective optimization algorithm, based on the quantum particle swarm optimization (QPSO) algorithm and adaptive ranks clone and neighbor list-based immune algorithm (NNIA2), is proposed. The contribution of this work is threefold. First, the vicinity distance was used instead of the crowding distance to update the archived optimal solutions in the QPSO algorithm. The archived optimal solutions are updated and maintained by using the dynamic vicinity distance based m-nearest neighbor list in the QPSO algorithm. Secondly, an adaptive dynamic threshold of unfitness function for constraint handling is introduced in the process. It is related to the evolution algebra and the feasible solution. Thirdly, a new metric called the distribution metric is proposed to depict the diversity and distribution of the Pareto optimal. In order to verify the validity and feasibility of the QPSO-NNIA2 algorithm, we compare it with the QPSO, NNIA2, NSGA-II, MOEA/D, and SPEA2 algorithms in solving unconstrained and constrained multi-objective problems. The simulation results show that the QPSO-NNIA2 algorithm achieves superior convergence and superior performance by three metrics compared to other algorithms.

scholarly journals A Hybrid Multi-Objective Optimization Method Based on NSGA-II Algorithm and Entropy Weighted TOPSIS for Lightweight Design of Dump Truck Carriage

Machines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 156
Author(s):  
Rongchao Jiang ◽  
Shukun Ci ◽  
Dawei Liu ◽  
Xiaodong Cheng ◽  
Zhenkuan Pan
Keyword(s):  
Optimal Design ◽  
Lightweight Design ◽  
Dump Truck ◽  
Strength Analysis ◽  
Multi Objective Optimization ◽  
Pareto Solutions ◽  
Entropy Weight ◽  
Nsga Ii ◽  
Multi Objective ◽  
Entropy Weighted

The lightweight design of vehicle components is regarded as a complex optimization problem, which usually needs to achieve two or more optimization objectives. It can be firstly solved by a multi-objective optimization algorithm for generating Pareto solutions, before then seeking the optimal design. However, it is difficult to determine the optimal design for lack of engineering knowledge about ideal and nadir values. Therefore, this paper proposes a multi-objective optimization procedure combined with the NSGA-II algorithm with entropy weighted TOPSIS for the lightweight design of the dump truck carriage. The finite element model of the dump truck carriage was firstly developed for modal analysis under unconstrained free state and strength analysis under the full load and lifting conditions. On this basis, the multi-objective lightweight optimization of the dump truck carriage was carried out based on the Kriging surrogate model and the NSGA-II algorithm. Then, the entropy weight TOPSIS method was employed to select the optimal design of the dump truck from Pareto solutions. The results show that the optimized dump truck carriage achieves a remarkable mass reduction of 81 kg, as much as 3.7%, while its first-order natural frequency and strength performance are slightly improved compared with the original model. Accordingly, the proposed procedure provides an effective way for vehicle lightweight design.

Framework for the optimization of online computable models

2014 ◽  
Vol 33 (3) ◽  
pp. 745-758 ◽  
Author(s):  
Benoit Delinchant ◽  
Frédéric Wurtz ◽  
João Vasconcelos ◽  
Jean-Louis Coulomb
Keyword(s):  
Simulation Model ◽  
Web Service ◽  
Optimization Algorithm ◽  
Design Methodology ◽  
Optimization Algorithms ◽  
Software Component ◽  
The Internet ◽  
Content Type ◽  
Optimization Framework

Purpose – The purpose of this paper is to make easily accessible models to test and compare the optimization algorithms we develop. Design/methodology/approach – For this, the paper proposes an optimization framework based on software component, web service, and plugin to exploit these models in different environments. Findings – The paper illustrates the discussion with optimizations in Matlab™ and R (www.r-project.org) of a transformer described and exploitable from the internet. Originality/value – The originality is to make easy implementation of simulation model and optimization algorithm coupling using software component, web service, and plugin.

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