MATEC Web Conf.
Volume 192, 2018The 4th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”
|Number of page(s)||4|
|Section||Track 1: Industrial Engineering, Materials and Manufacturing|
|Published online||14 August 2018|
A comparison of latin hypercube sampling techniques for a supply chain network design problem
Industrial Engineering Department, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand
2 Graduate School of Management and Innovation, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Corresponding author: firstname.lastname@example.org
Currently, supply chain network design becomes more complex. In designing a supply chain network to withstand changing events, it is necessary to consider the uncertainties and risks that cause network disruptions from unexpected events. The current research related to the designing problem considers network disruptions using Monte Carlo Sampling (MCS) or Latin Hypercube Sampling (LHS) techniques. Both have a disadvantage that sample points or disruption locations are not scattered entirely sample space leading to high variation in objective function values. The purpose of this study is to apply a modified LHS or Improved Distributed Hypercube Sampling (IHS) techniques to reduce the variation. The results show that IHS techniques provide smaller standard deviation than that of the LHS technique. In addition, IHS can reduce not only the number of sample size but also and the computational time.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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