Multi-objective, multi-domain genetic optimization of a hydraulic rescue spreader

Thomas A. Sullivan; James D. Van De Ven

doi:10.1016/j.mechmachtheory.2014.04.019

Multi-objective, multi-domain genetic optimization of a hydraulic rescue spreader

Thomas A. Sullivan, James D. Van De Ven

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

In this paper, general strategies are presented by which a multi-domain, multi-objective, mechanism-based optimization problem may be efficiently formulated and solved by means of a genetic algorithm. These strategies include integration of traditional precision position techniques with genetic optimization, efficient selection of design variables and search bounds, and a nested optimization structure. A case study illustrating these methods is presented in which a hydraulic rescue spreader is simultaneously optimized for four objectives relating to structural efficiency and kinematic behavior. The solution obtained is shown to be equal or superior to a comparable commercially available device with respect to all four objectives.

Original language	English (US)
Pages (from-to)	35-51
Number of pages	17
Journal	Mechanism and Machine Theory
Volume	80
DOIs	https://doi.org/10.1016/j.mechmachtheory.2014.04.019
State	Published - Oct 2014

Bibliographical note

Funding Information:
This work was supported by the Defense Advanced Research Projects Agency under Contract # W31P4Q-11-C-0060 .

Keywords

Evolutionary techniques
Genetic algorithms
Mechanism optimization
Mechanism synthesis
Multi-domain optimization
Multi-objective optimization

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10.1016/j.mechmachtheory.2014.04.019

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title = "Multi-objective, multi-domain genetic optimization of a hydraulic rescue spreader",

abstract = "In this paper, general strategies are presented by which a multi-domain, multi-objective, mechanism-based optimization problem may be efficiently formulated and solved by means of a genetic algorithm. These strategies include integration of traditional precision position techniques with genetic optimization, efficient selection of design variables and search bounds, and a nested optimization structure. A case study illustrating these methods is presented in which a hydraulic rescue spreader is simultaneously optimized for four objectives relating to structural efficiency and kinematic behavior. The solution obtained is shown to be equal or superior to a comparable commercially available device with respect to all four objectives.",

keywords = "Evolutionary techniques, Genetic algorithms, Mechanism optimization, Mechanism synthesis, Multi-domain optimization, Multi-objective optimization",

author = "Sullivan, {Thomas A.} and {Van De Ven}, {James D.}",

note = "Funding Information: This work was supported by the Defense Advanced Research Projects Agency under Contract # W31P4Q-11-C-0060 .",

year = "2014",

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doi = "10.1016/j.mechmachtheory.2014.04.019",

language = "English (US)",

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T1 - Multi-objective, multi-domain genetic optimization of a hydraulic rescue spreader

AU - Sullivan, Thomas A.

AU - Van De Ven, James D.

N1 - Funding Information: This work was supported by the Defense Advanced Research Projects Agency under Contract # W31P4Q-11-C-0060 .

PY - 2014/10

Y1 - 2014/10

N2 - In this paper, general strategies are presented by which a multi-domain, multi-objective, mechanism-based optimization problem may be efficiently formulated and solved by means of a genetic algorithm. These strategies include integration of traditional precision position techniques with genetic optimization, efficient selection of design variables and search bounds, and a nested optimization structure. A case study illustrating these methods is presented in which a hydraulic rescue spreader is simultaneously optimized for four objectives relating to structural efficiency and kinematic behavior. The solution obtained is shown to be equal or superior to a comparable commercially available device with respect to all four objectives.

AB - In this paper, general strategies are presented by which a multi-domain, multi-objective, mechanism-based optimization problem may be efficiently formulated and solved by means of a genetic algorithm. These strategies include integration of traditional precision position techniques with genetic optimization, efficient selection of design variables and search bounds, and a nested optimization structure. A case study illustrating these methods is presented in which a hydraulic rescue spreader is simultaneously optimized for four objectives relating to structural efficiency and kinematic behavior. The solution obtained is shown to be equal or superior to a comparable commercially available device with respect to all four objectives.

KW - Evolutionary techniques

KW - Genetic algorithms

KW - Mechanism optimization

KW - Mechanism synthesis

KW - Multi-domain optimization

KW - Multi-objective optimization

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DO - 10.1016/j.mechmachtheory.2014.04.019

M3 - Article

AN - SCOPUS:84901426226

SN - 0094-114X

VL - 80

SP - 35

EP - 51

JO - Mechanism and Machine Theory

JF - Mechanism and Machine Theory

ER -

Multi-objective, multi-domain genetic optimization of a hydraulic rescue spreader

Abstract

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Keywords

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