A New Approach for Low-Dimensional Constrained Engineering Design Optimization Using Design and Analysis of Simulation Experiments

Authors

Amir Parnianifard^{1, *,} , Ratchatin Chancharoen^2, , Gridsada Phanomchoeng², Lunchakorn Wuttisittikulkij^{1, *}

¹Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

²Department of Mechanical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

^*Corresponding authors. Email: Lunchakorn.W@chula.ac.th; amir.p@chula.ac.th

DOI

10.2991/ijcis.d.201014.001How to use a DOI?

Keywords

Constrained optimization; Surrogates; Kriging; Computationally expensive function; Global optimization

Abstract

The number of function evaluations in many industrial applications of simulation-based optimization problems is strictly limited. Therefore, only little analytical information on objective and constraint functions is available. This paper presents an adaptive algorithm called the Surrogate-Based Constrained Global-Optimization (SCGO) method to solve black-box constrained simulation-based optimization problems involving computationally expensive objective function and inequality constraints. Firstly, Kriging surrogate is constructed over a new overall objective function (called loss function) to approximate the behavior of a true model. Then, an adaptive approach is provided to improve the optimal results sequentially while enforcing a feasible solution. The SCGO method is tested on several classical engineering design problems namely design of a tension/compression spring, design of a welded beam, design of a pressure vessel, and three-bar truss design. The results demonstrate that SCGO has advantages in solving the costly constrained problems and needs less costly function evaluations. Optimization results prove that the proposed algorithm is very competitive compared to the state-of-the-art metaheuristic algorithms.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Amir Parnianifard
AU  - Ratchatin Chancharoen
AU  - Gridsada Phanomchoeng
AU  - Lunchakorn Wuttisittikulkij
PY  - 2020
DA  - 2020/10/23
TI  - A New Approach for Low-Dimensional Constrained Engineering Design Optimization Using Design and Analysis of Simulation Experiments
JO  - International Journal of Computational Intelligence Systems
SP  - 1663
EP  - 1678
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201014.001
DO  - 10.2991/ijcis.d.201014.001
ID  - Parnianifard2020
ER  -