In engineering design problems, performance functions evaluate the quality of designs. Among the designs, some of them are classified as good designs if responses from performance functions satisfy a target point or range. An infinite set of good designs in the design space is defined as a solution space of the design problem. In practice, since the performance functions are analytical models or black-box simulations which are computationally expensive, it is difficult to obtain a complete solution space. In this paper, a method that finds a finite set of good designs, which is included in a solution space, is proposed. The method formulates the problem as optimization problems and utilizes gray wolf optimizer (GWO) in the way of design exploration. Target points of the exploration process are defined by clustering intermediate solutions for every iteration. The method is tested with a simple two-dimensional problem and an automotive vehicle design problem to validate and check the quality of solution points.
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September 2019
Research-Article
Multiple Target Exploration Approach for Design Exploration Using a Swarm Intelligence and Clustering
Hyeongmin Han,
Hyeongmin Han
Industrial and Enterprise Systems Engineering,
Urbana, IL 61801
e-mail: hhan19@illinois.edu
University of Illinois at Urbana-Champaign
,Urbana, IL 61801
e-mail: hhan19@illinois.edu
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Sehyun Chang,
Sehyun Chang
Global R&D Master, Automotive R&D Division,
Namyang-eup,
Hwaseong-si 18280,
Gyeonggi-do,
e-mail: suschang@hyundai.com
Hyundai Motor Company
,Namyang-eup,
Hwaseong-si 18280,
Gyeonggi-do,
Korea
e-mail: suschang@hyundai.com
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Harrison Kim
Harrison Kim
1
Professor
Industrial and Enterprise Systems Engineering,
Urbana, IL 61801
e-mail: hmkim@illinois.edu
Industrial and Enterprise Systems Engineering,
University of Illinois at Urbana-Champaign
,Urbana, IL 61801
e-mail: hmkim@illinois.edu
1Corresponding author.
Search for other works by this author on:
Hyeongmin Han
Industrial and Enterprise Systems Engineering,
Urbana, IL 61801
e-mail: hhan19@illinois.edu
University of Illinois at Urbana-Champaign
,Urbana, IL 61801
e-mail: hhan19@illinois.edu
Sehyun Chang
Global R&D Master, Automotive R&D Division,
Namyang-eup,
Hwaseong-si 18280,
Gyeonggi-do,
e-mail: suschang@hyundai.com
Hyundai Motor Company
,Namyang-eup,
Hwaseong-si 18280,
Gyeonggi-do,
Korea
e-mail: suschang@hyundai.com
Harrison Kim
Professor
Industrial and Enterprise Systems Engineering,
Urbana, IL 61801
e-mail: hmkim@illinois.edu
Industrial and Enterprise Systems Engineering,
University of Illinois at Urbana-Champaign
,Urbana, IL 61801
e-mail: hmkim@illinois.edu
1Corresponding author.
Contributed by the Design Automation Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received April 8, 2018; final manuscript received March 8, 2019; published online April 22, 2019. Assoc. Editor: Mian Li.
J. Mech. Des. Sep 2019, 141(9): 091401 (9 pages)
Published Online: April 22, 2019
Article history
Received:
April 8, 2018
Revision Received:
March 8, 2019
Accepted:
March 12, 2019
Citation
Han, H., Chang, S., and Kim, H. (April 22, 2019). "Multiple Target Exploration Approach for Design Exploration Using a Swarm Intelligence and Clustering." ASME. J. Mech. Des. September 2019; 141(9): 091401. https://doi.org/10.1115/1.4043201
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