Combination of Metaheuristics to the Optimal Design of Analog and RF Circuits

2015 ◽  
pp. 210-234 ◽  
Author(s):  
Amin Sallem ◽  
Mouna Kotti ◽  
Mourad Fakhfakh ◽  
Esteban Tlelo-Cuautle ◽  
Patrick Siarry
Keyword(s):  
Optimal Design ◽  
Pareto Front ◽  
Rf Circuits ◽  
Multi Objective

Multi-objective metaheuristics are over and over again used by analog designers. They allow generating a set of non-dominated solutions (i.e. the Pareto front). In this chapter, the authors highlight the fact, via the application of six multi-objective algorithms to the optimization of conflicting performances of four analog and RF circuits, that the generated fronts highly depend on the used algorithm. They propose a solution consisting of combining metaheuristics to generate a “better” front by merging results obtained thanks to different algorithms and the application of a dominance routine. Viability of the proposed idea is shown through examples.

2104 A Study on the Visualization of the Pareto Front in Multi-Objective Optimal Design for OLED

2014 ◽  
Vol 2014.24 (0) ◽  
pp. _2104-1_-_2104-5_
Author(s):  
Noka NAGASAKI ◽  
Garuda FUJII ◽  
Masayuki NAKAMURA
Keyword(s):  
Optimal Design ◽  
Pareto Front ◽  
Multi Objective

scholarly journals Optimal Design of IPMSM for EV Using Subdivided Kriging Multi-Objective Optimization

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1490
Author(s):  
Jong-Min Ahn ◽  
Myung-Ki Baek ◽  
Sang-Hun Park ◽  
Dong-Kuk Lim
Keyword(s):  
Optimal Design ◽  
Objective Function ◽  
Pareto Front ◽  
Permanent Magnet Synchronous Motor ◽  
Kriging Model ◽  
Superior Performance ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Design Variables ◽  
Interior Permanent Magnet

In this paper, subdivided kriging multi-objective optimization (SKMOO) is proposed for the optimal design of interior permanent magnet synchronous motor (IPMSM). The SKMOO with surrogate kriging model can obtain a uniform and accurate pareto front set with a reduced computation cost compared to conventional algorithms which directly adds the solution in the objective function area. In other words, the proposed algorithm uses a kriging surrogate model, so it is possible to know which design variables have the value of the objective function on the blank space. Therefore, the solution can be added directly in the objective function area. In the SKMOO algorithm, a non-dominated sorting method is used to find the pareto front set and the fill blank method is applied to prevent premature convergence. In addition, the subdivided kriging grid is proposed to make a well-distributed and more precise pareto front set. Superior performance of the SKMOO is confirmed by compared conventional multi objective optimization (MOO) algorithms with test functions and are applied to the optimal design of IPMSM for electric vehicle.

scholarly journals A Multi-Objective Approach toward Optimal Design of Sustainable Integrated Biodiesel/Diesel Supply Chain Based on First- and Second-Generation Feedstock with Solid Waste Use

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2261
Author(s):  
Evgeniy Ganev ◽  
Boyan Ivanov ◽  
Natasha Vaklieva-Bancheva ◽  
Elisaveta Kirilova ◽  
Yunzile Dzhelil
Keyword(s):  
Supply Chain ◽  
Optimal Design ◽  
Solid Waste ◽  
Second Generation ◽  
Agricultural Land ◽  
Optimization Problems ◽  
Biodiesel Production ◽  
Mixed Integer ◽  
Economic Criterion ◽  
Multi Objective

This study proposes a multi-objective approach for the optimal design of a sustainable Integrated Biodiesel/Diesel Supply Chain (IBDSC) based on first- (sunflower and rapeseed) and second-generation (waste cooking oil and animal fat) feedstocks with solid waste use. It includes mixed-integer linear programming (MILP) models of the economic, environmental and social impact of IBDSC, and respective criteria defined in terms of costs. The purpose is to obtain the optimal number, sizes and locations of bio-refineries and solid waste plants; the areas and amounts of feedstocks needed for biodiesel production; and the transportation mode. The approach is applied on a real case study in which the territory of Bulgaria with its 27 districts is considered. Optimization problems are formulated for a 5-year period using either environmental or economic criteria and the remainder are defined as constraints. The obtained results show that in the case of the economic criterion, 14% of the agricultural land should be used for sunflower and 2% for rapeseed cultivation, while for the environmental case, 12% should be used for rapeseed and 3% for sunflower. In this case, the price of biodiesel is 14% higher, and the generated pollutants are 6.6% lower. The optimal transport for both cases is rail.

Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

2013 ◽  
Vol 307 ◽  
pp. 161-165
Author(s):  
Hai Jin ◽  
Jin Fa Xie
Keyword(s):  
Optimization Design ◽  
Pareto Front ◽  
Layout Optimization ◽  
Multiple Objective ◽  
Multi Objective Optimization ◽  
Layout Problem ◽  
Basic Principles ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Set Up

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

Randomized multi-objective optimal design of a novel deployable truss

2012 ◽  
Vol 227 (11) ◽  
pp. 1720-1736 ◽  
Author(s):  
Hailin Huang ◽  
Bing Li ◽  
Zongquan Deng ◽  
Rongqiang Liu
Keyword(s):  
Optimal Design ◽  
Multi Objective
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