A cost-effective decision-making algorithm for an RFID-enabled HMSC network design. A multi-objective approach
| Published date | 16 October 2017 |
| DOI | https://doi.org/10.1108/IMDS-02-2016-0074 |
| Date | 16 October 2017 |
| Pages | 1782-1799 |
| Author | Ahmed Mohammed,Qian Wang,Xiaodong Li |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
A cost-effective decision-making
algorithm for an RFID-enabled
HMSC network design
A multi-objective approach
Ahmed Mohammed and Qian Wang
School of Engineering, University of Portsmouth, Portsmouth, UK, and
Xiaodong Li
Department of Mathematics, University of Portsmouth, Portsmouth, UK
Abstract
Purpose –The purpose of this pape r is to investigate the econo mic feasibility of a three-ec helon Halal Meat
Supply Chain (HMSC) ne twork that is monitored by a pro posed radio frequency identi fication (RFID)-based
management system for e nhancing the integrity traceability of Hala l meat products and to maximize the
average integrity num ber of Halal meat products, maximize the ret urn of investment (ROI), maximize the
capacity utilization of fa cilities and minimize the to tal investment cost of the prop osed RFID-monitoring
system. The location- allocation problem of fa cilities needs also to be resolved in conjuncti on with the
quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers.
Design/methodology/approach –First, a deterministic multi-objectivemixed integer linear programming
model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised
solution basedon four conflicting objectivesas described above. Second, a stochasticprogramming model was
developed and usedfor examining the impact on the number of Halal meat products by altering the value of
integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for
acquisitionof non-inferior solutions obtained fromthe developed models. Furthermore, theMax-Min approach
was used for selecting the best solutionamong them.
Findings –The research outcome shows the applicability of the developed models using a real case study.
Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the
HMSC network.
Research limitations/implications –This work addresses interesting avenues for further research
on exploring the HMSC net work design under diffe rent types of uncertai nties and transportati on
means. Also, environm entalism has been beco ming increasingly a sign ificant global prob lem in the
present century. Thus, the pr esented model could be extended to include the environm ental aspects as an
objective function.
Practical implications –The model can be utilized for food supply chain designers. Also, it could be
applied to realistic problems in the field of supply chain management.
Originality/value –Although there were a few studies focusing on the configuration of a number of
HMSC networks, this area is overl ooked by researchers. The study shows the develope d methodology can
be a useful tool for designers to det ermine a cost-effective design of food supply chain ne tworks.
Keywords Multi-objective optimization, RFID, Halal, Supply chain design, Facility location-allocation problem,
Stochastic programming
Paper type Research paper
Industrial Management & Data
Systems
Vol. 117 No. 9, 2017
pp. 1782-1799
Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-02-2016-0074
Received 21 February 2016
Revised 31 July 2016
3 October 2016
16 October 2016
Accepted 17 October 2016
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
© Ahmed Mohammed, Qian Wang and Xiaodong Li. Published by Emerald Publishing Limited. This
article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may
reproduce, distribute, translate and create derivative works of this article (for both commercial & non-
commercial purposes), subject to full attribution to the original publication and authors. The full terms
of this licence may be seen at: http://creativecommons.org/licences/by/4.0/legalcode
The authors would like to express the authors’gratitude to the Higher Committee for Education
Development (HCED) in Iraq for the financial support in this study. Also, the authors would like to
thank the anonymous referees whose thorough reviews and insightful comments made a valuable
contribution to this paper.
1782
IMDS
117,9
Nomenclature
Deterministic model
Sets
Iset of farms i∈I
Jset of abattoirs j∈J
Kset of retailers k∈K
Given parameters
CE;a
iRFID equipment (E) cost required
for farm i
CE;b
jRFID equipment (E) cost required
for abattoir j
CI;a
iRFID implementation (I)cost
required for farm i
CI;b
jRFID implementation (I)cost
required for abattoir j
Ct
iRFID tag cost per item at farm i
Ct
jRFID tag cost per item at abattoir j
CT;u
ij unit transportation (T) cost per mile
from farm ito abattoir j
CT;v
jk unit transportation (T) cost per mile
from abattoir jto retailer k
Ch;a
ihandling cost per item at farm i
Ch;b
jhandling cost per item at abattoir j
du
ij travel distance of livestock from
farm ito abattoir j
dv
jk travel distance of Halal meat
products from abattoir jto retailer k
Wtransportation capacity per vehicle
Sa
imaximum supply capacity of farm i
Sb
jmaximum supply capacity of
abattoir j
Db
jminimum demand of abattoir j
Dg
kminimum demand of retailer k
Pu
ij integrity percentage of live stock
through first transportation link u
from farm ito abattoir j
Pv
jk integrity percentage of meat
products through second
transportation link vfrom abattoir
jto retailer k
Ra
ireturn of investment for farm i
Rb
jreturn of investment per item for
abattoir j
Decision variables
xu
ij quantity of units transported
through the first transportation
link ufrom farm ito abattoir j
xv
jk quantity of units transported
through second transportation link
vfrom abattoir jto retailer k
ya
i{1: if farm iis open, 0: otherwise
yb
j{1: if abattoir jis open, 0: otherwise
Stochastic model
Sets
Ωset of scenarios ξ∈Ω
Given parameters
Pu
ijxintegrity percentage of live stock
through the first transportation
link ufrom farm ito abattoir jin
scenario ξ
Pv
jkxintegrity percentage of meat
products through the second
transportation link vfrom abattoir
jto retailer kin scenario ξ
Prob ξProbability of scenario ξ
Decision variables
xu
ijxquantity of units transported
through the first transportation
link ufrom farm ito abattoir jin
scenario ξ
xv
jkxquantity of units transported
through the second transportation
link v from abattoir jto retailer kin
scenario ξ
ya
ix{1: if farm iin scenario ξis open,
0: otherwise
yb
jx{1: if abattoir jin scenario ξis open,
0: otherwise
1. Introduction
Today, a cost-effective design of efficient food supply chain networks is crucial for
retailers to maintain a share in the increasingly competitive market. The design of
a food supply chain network, however, often involves a trade-off decision-making
process by minimizing its total cost and transportation time, whilst maintaining
quality of food to be delivered to customers. In practice, such a trade-off decision may
also vary over time due to the consistent change in conditions of the unpredictable
market. Thus, the performance of a supply chain network needs also to be evaluated
1783
RFID-enabled
HMSC network
design
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