Journal of Mechanical Science and Technology, ( ISI ), Volume (25), No (12), Year (2011-8) , Pages (2971-2977)

Title : ( Multiobjective optimization for force and moment balance of a four-bar linkage using evolutionary algorithms )

Authors: Mohammad Reza Farmani , Abdolrahman Jaamialahmadi , Meisam Babaie ,

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Abstract

In this study, force and moment balance of a planar four-bar linkage is implemented using evolutionary algorithms . In the current problem, the concepts of inertia counterweights and physical pendulum are utilized to complete balance of all mass effects, independent of input angular velocity. A proposed multiobjective particle swarm optimization, and non-dominated sorting genetic algorithm II are applied to minimize two objective functions subject to some design constraints. The applied algorithms produced a set of feasible solutions called pareto optimal solutions for the design problem. Finally, a fuzzy decision maker is utilized to select the best solution among the obtained pareto solutions. The results show that optimal solutions minimize the weights of applied counterweights and eliminate both shaking forces and moments transmitted to the ground, simultaneously.

Keywords

, Force and moment balance; Four, bar linkage; Multiobjective particle swarm optimization; Non, dominated sorting genetic algorithm; Fuzzy decision maker
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@article{paperid:1023655,
author = {Mohammad Reza Farmani and Jaamialahmadi, Abdolrahman and Meisam Babaie},
title = {Multiobjective optimization for force and moment balance of a four-bar linkage using evolutionary algorithms},
journal = {Journal of Mechanical Science and Technology},
year = {2011},
volume = {25},
number = {12},
month = {August},
issn = {1738-494X},
pages = {2971--2977},
numpages = {6},
keywords = {Force and moment balance; Four-bar linkage; Multiobjective particle swarm optimization; Non-dominated sorting genetic algorithm; Fuzzy decision maker},
}

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%0 Journal Article
%T Multiobjective optimization for force and moment balance of a four-bar linkage using evolutionary algorithms
%A Mohammad Reza Farmani
%A Jaamialahmadi, Abdolrahman
%A Meisam Babaie
%J Journal of Mechanical Science and Technology
%@ 1738-494X
%D 2011

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