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Title of Journal: Struct Multidisc Optim

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Abbravation: Structural and Multidisciplinary Optimization

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Springer Berlin Heidelberg

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DOI

10.1016/0301-0104(85)87010-5

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ISSN

1615-1488

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A multiobjective differential evolution approach

Authors: I Gholaminezhad A Jamali
Publish Date: 2015/06/20
Volume: 52, Issue: 5, Pages: 861-877
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Abstract

In this paper a new multiobjective uniformdiversity differential evolution MUDE algorithm is proposed and used for Pareto optimum design of mechanisms The proposed algorithm uses a diversity preserving mechanism called the εelimination algorithm to improve the population diversity among the obtained Pareto front The proposed algorithm is firstly tested on some constrained and unconstrained benchmarks proposed for the special session and competition on multiobjective optimizers held under IEEE CEC 2009 The inverted generational distance IGD measure is used to assess the performance of the algorithm Secondly the proposed algorithm has been used for multiobjective optimization of two different combinatorial case studies The first case contains a twodegree of freedom leg mechanism with springs Three conflicting objective functions that have been considered for Pareto optimization are namely leg size vertical actuating force and the peak crank torque The second case is a twofinger robot gripper mechanism with two conflicting objectives which are the difference between the maximum and minimum gripping force and the transmission ratio of actuated and experienced gripper forces Comparisons of obtained Pareto fronts using the method of this work with those obtained in other references show significant improvementsWhere l min and l max are the minimum and maximum value of link EJ In addition in the above equations it is assumed that YH is at its midrange position The constant parameters of the constraints are as follows HSC1 = 1 HSC2 = 13 HSC3 = 1 HSC4 = 13 HSC5 = −03 HSC6 = 01 HSC7 = 01 HSC8 = 06where yx z = 2 e + f + c sinδ + β is the displacement of gripper ends Ymin and Ymax are maximum and minimum dimensions of gripping object YG is the maximum range of gripper ends displacement and FG is the assumed minimal gripping force More description of constraints could be found in Osyczka 2002 Datta and Deb 2011

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  11. Aircraft wing box optimization considering uncertainty in surrogate models
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  17. A concurrent subspace collaborative optimization architecture to structural synthetical optimization design
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