A comparison of Latin hypercube sampling techniques for a supply chain network design problem

Kaewsuwan, Kantapit; Yuangyai, Chumpol; Janjarassuk, Udom; Rienkhemaniyom, Kanokporn

doi:10.1051/matecconf/201819201023

A comparison of Latin hypercube sampling techniques for a supply chain network design problem

Author(s)

Kaewsuwan, Kantapit

Yuangyai, Chumpol

Janjarassuk, Udom

Rienkhemaniyom, Kanokporn

Date Issued

August 14, 2018

Type

Conference Paper

DOI

10.1051/matecconf/201819201023

Abstract

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.

Citation

Matec Web of Conferences, 192, 2018