An approach for rush order acceptance decisions using simulation and multi-attribute utility theory

Faisal Aqlan, Abdulaziz Ahmed, Omar Ashour, Abdulrahman Shamsan, Mohammad M. Hamasha

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints.

Original languageEnglish (US)
Pages (from-to)613-630
Number of pages18
JournalEuropean Journal of Industrial Engineering
Volume11
Issue number5
DOIs
StatePublished - Jan 1 2017

Fingerprint

Customer satisfaction
Discrete event simulation
Profitability
Raw materials
Industry

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Cite this

@article{79d075993a2d4c92b6f895642268fa83,
title = "An approach for rush order acceptance decisions using simulation and multi-attribute utility theory",
abstract = "Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints.",
author = "Faisal Aqlan and Abdulaziz Ahmed and Omar Ashour and Abdulrahman Shamsan and Hamasha, {Mohammad M.}",
year = "2017",
month = "1",
day = "1",
doi = "10.1504/EJIE.2017.087680",
language = "English (US)",
volume = "11",
pages = "613--630",
journal = "European Journal of Industrial Engineering",
issn = "1751-5254",
publisher = "Inderscience Enterprises Ltd",
number = "5",

}

An approach for rush order acceptance decisions using simulation and multi-attribute utility theory. / Aqlan, Faisal; Ahmed, Abdulaziz; Ashour, Omar; Shamsan, Abdulrahman; Hamasha, Mohammad M.

In: European Journal of Industrial Engineering, Vol. 11, No. 5, 01.01.2017, p. 613-630.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An approach for rush order acceptance decisions using simulation and multi-attribute utility theory

AU - Aqlan, Faisal

AU - Ahmed, Abdulaziz

AU - Ashour, Omar

AU - Shamsan, Abdulrahman

AU - Hamasha, Mohammad M.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints.

AB - Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints.

UR - http://www.scopus.com/inward/record.url?scp=85032681116&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85032681116&partnerID=8YFLogxK

U2 - 10.1504/EJIE.2017.087680

DO - 10.1504/EJIE.2017.087680

M3 - Article

AN - SCOPUS:85032681116

VL - 11

SP - 613

EP - 630

JO - European Journal of Industrial Engineering

JF - European Journal of Industrial Engineering

SN - 1751-5254

IS - 5

ER -