Spatial Aggregation and Compactness of Census Areas with a Multiobjective Genetic Algorithm: A Case Study in Canada

2012 ◽  
Vol 39 (2) ◽  
pp. 376-392 ◽  
Author(s):  
Dilip Datta ◽  
Jacek Malczewski ◽  
José Rui Figueira
Keyword(s):  
Genetic Algorithm ◽  
Spatial Aggregation ◽  
Multiobjective Genetic Algorithm

Multiobjective genetic algorithm applied to inverse finite element analysis: T-joint welding case study

2021 ◽  
Author(s):  
Marcus Vinicius Ferreira de Moura ◽  
Leomardos Santos Marques ◽  
Bruno Henrique Groenner Barbosa ◽  
Ricardo Rodrigues Magalhães
Keyword(s):  
Genetic Algorithm ◽  
Finite Element Analysis ◽  
Finite Element ◽  
Element Analysis ◽  
Multiobjective Genetic Algorithm ◽  
Inverse Finite Element Analysis

A web-based assembly planning approach

2008 ◽  
Vol 222 (3) ◽  
pp. 427-440 ◽  
Author(s):  
C Lu ◽  
Y S Wong ◽  
J Y H Fuh
Keyword(s):  
Genetic Algorithm ◽  
Assembly Planning ◽  
Working Mechanism ◽  
Web Based ◽  
Multiobjective Genetic Algorithm ◽  
Geographically Dispersed ◽  
Planning Approach ◽  
Planning Task

This paper presents a web-based assembly planning approach that enables geographically dispersed planners to carry out the assembly planning task collaboratively and concurrently based on an assembly planning approach using a multiobjective genetic algorithm. Issues in web-based assembly planning are discussed and a workflow is presented. A framework is proposed for web-based assembly planning and the working mechanism is discussed. Finally, a case study is given to verify the proposed approach.

Decomposition-Based Assembly Synthesis of Multiple Structures for Minimum Manufacturing Cost

2004 ◽  
Vol 127 (4) ◽  
pp. 572-579 ◽  
Author(s):  
Onur L. Cetin ◽  
Kazuhiro Saitou
Keyword(s):  
Genetic Algorithm ◽  
Early Identification ◽  
Economies Of Scale ◽  
Structural Strength ◽  
Manufacturing Cost ◽  
Manufacturing Costs ◽  
Multiobjective Genetic Algorithm ◽  
Trade Offs ◽  
Multiple Structures

An extension of decomposition-based assembly synthesis for structural modularity is presented where the early identification of shareable components within multiple structures is posed as an outcome of the minimization of estimated manufacturing costs. The manufacturing costs of components are estimated under given production volumes considering the economies of scale. Multiple structures are simultaneously decomposed, and the types of welded joints at component interfaces are selected from a given library, in order to minimize the overall manufacturing cost and the reduction of structural strength due to the introduction of joints. A multiobjective genetic algorithm is used to allow effective examination of trade-offs between manufacturing cost and structural strength. A new joint-oriented representation of structures combined with a “direct” crossover is introduced to enhance the efficiency of the search. A preliminary case study with two simplified aluminum space frame automotive bodies is presented to demonstrate that not all types of component sharing are economically justifiable under a certain production scenario.

scholarly journals Hybrid Seven-bar Press Mechanism

2018 ◽  
Vol 12 (3) ◽  
pp. 181-187
Author(s):  
M. Erkan Kütük ◽  
L. Canan Dülger
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Optimization ◽  
Hybrid System ◽  
Degrees Of Freedom ◽  
Dimensional Synthesis ◽  
Design Variables ◽  
Optimization Study ◽  
Metal Stamping

An optimization study with kinetostatic analysis is performed on hybrid seven-bar press mechanism. This study is based on previous studies performed on planar hybrid seven-bar linkage. Dimensional synthesis is performed, and optimum link lengths for the mechanism are found. Optimization study is performed by using genetic algorithm (GA). Genetic Algorithm Toolbox is used with Optimization Toolbox in MATLAB®. The design variables and the constraints are used during design optimization. The objective function is determined and eight precision points are used. A seven-bar linkage system with two degrees of freedom is chosen as an example. Metal stamping operation with a dwell is taken as the case study. Having completed optimization, the kinetostatic analysis is performed. All forces on the links and the crank torques are calculated on the hybrid system with the optimized link lengths

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

Sign in / Sign up

Export Citation Format

Share Document