Multi-objective production-distribution planning based on vendor-managed inventory strategy in a supply chain
| DOI | https://doi.org/10.1108/IMDS-03-2015-0073 |
| Published date | 13 July 2015 |
| Date | 13 July 2015 |
| Pages | 1086-1112 |
| Author | Amir Hossein Niknamfar |
| Subject Matter | Information & knowledge management,Information systems,Data management systems |
Multi-objective production-
distribution planning based on
vendor-managed inventory
strategy in a supply chain
Amir Hossein Niknamfar
Young Researchers and Elite Club, Qazvin Branch,
Islamic Azad University, Qazvin, Iran
Abstract
Purpose –The production-distribution (P-D) problems are two critical problems in many industries,
in particular, in manufacturing systems and the supply chain management. In previous researches
on P-D planning, the demands of the retailers and their inventory levels have less been controlled.
This may lead into huge challenges for a P-D plan such as the bullwhip effects. Therefore, to remove
this challenge, the purpose of this paper is to integrate a P-D planning and the vendor-managed
inventory (VMI) as a strong strategy to manage the bullwhip effects in supply chains. The proposed
P-D-VMI aims to minimize the total cost of the manufacturer, the total cost of the retailers, and the total
distribution time simultaneously.
Design/methodology/approach –This paper presents a multi-objective non-linear model for a P-D
planning in a three-level supply chain including several external suppliers at the first level, a single
manufacturer at the second level, and multi-retailer at the third level. A non-dominated sorting genetic
algorithmand a non-dominated rankinggenetic algorithm aredesigned and tuned to solvethe proposed
problem. Then,their performances are statistically analyzed and ranked by the TOPSIS method.
Findings –The applicability of the proposed model and solution methodologies are demonstrated
under several problems. A sensitivity analysis indicates the market scale and demand elasticity have
a substantial impact on the total cost of the manufacturer in the proposed P-D-VMI.
Originality/value –Although the P-D planning is a popular approach, there has been little discussion
about the P-D planning based on VMI so far. The novelty comes from developing a practical and new
approach that integrates the P-D planning and VMI.
Keywords Supply chain management, Non-dominated sorting genetic algorithm,
Production-distribution planning, Vendor-managed inventory
Paper type Research paper
1. Introduction
In the real world, the production and distribution problems are two critical problems in
many industries, in particular, in manufacturing systems and supply chain management
processes (Kazemi et al., 2009). In this regard, the importance of optimization in production
planning and distribution is studied by Boudia (2008) in supply chain management
especially for manufacturing systems. In the first problem, decisions have to be made about
regular working time and overtime of the employees, subcontracting production, machine
capacity consideration, and firing and hiring of employees for a definite planning horizon
that is usually a one year period (Varthanan et al., 2012). In the second problem, on the other
hand, distribution planning decisions on which facilities would fulfill the demands of their
Industrial Management & Data
Systems
Vol. 115 No. 6, 2015
pp. 1086-1112
©Emerald Group Publishing Limited
0263-5577
DOI 10.1108/IMDS-03-2015-0073
Received 11 March 2015
Revised 11 April 2015
Accepted 20 April 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
The authors would like to acknowledge the efforts and the consideration of the editor and all of
the anonymous reviewers for their valuable comments and suggestions to improve the quality of
the paper.
1086
IMDS
115,6
markets (Fahimnia et al., 2013; Bilgen and Günther, 2010). However, the existing researches
ontheproductionplanningonlydealwithproductionplanningseparately,andthey
did not take into account the interrelated nature of production and distribution systems
simultaneously. This gap often leads to inadequate and unreliable results, whereas the
aggregate production-distribution (P-D) would allow better planning and scheduling for
manufacturers (Aliev et al., 2007; Fahimnia et al., 2013). In real world, the P-D planning is
one of the most important problems in manufacturing systems and supply chains (Kazemi
et al., 2009) that has received an extensive attention of both practitioners and researchers.
Despite the advantages of the P-D planning, there are some gaps and challenges
in this field yet. In most researches on P-D planning, especially in the supply chains
including a single manufacturer and multi-retailer, the demands of the retailers and
their inventory levels have less been controlled (Aliev et al., 2007; Bashiri et al., 2012;
Kumar and Tiwari, 2013; Niknamfar et al., 2014).
In this regard, the fluctuations of retailers’orders and the bullwhip effects are
generated. Consequently, this may lead into huge challenges for a P-D plan even for
setting an applicable P-D plan. On the other hand, the demand has usually been
assumed as deterministic, fuzzy, or probabilistic and less attention has been paid to
the factors affecting it such as market scales, demand elasticity, and retail prices. It is
worthwhile to mention that in real world, these parameters have significant influence
on the demand. Here, it is worthwhile to mention that one of the programs for
enhancing the manufacturing system efficiency is the vendor-managed inventory
(VMI) approach (Liao et al., 2011) that is a well-known practice in industry (Lee and Ren,
2011). Besides, it is a common policy in real world to reduce the bullwhip effects
(Sadeghi et al., 2013).
In a VMI program, the manufacturer (i.e. vendor) manages the inventory at hand
the retailer and decides when and how much to replenish (Bichescu and Fry, 2009).
The advantage of VMI is that the manufacturer is able to determine the time and
quantity of replenishment and thus to manage the retailer’s inventory and the demand
and thus the point of sales data. As a result, the vendor can coordinate his long-term
plans and control the day-to-day flow of products and materials. On the other hand,
retailers incur no ordering cost and are guarded against the excessive inventory cos t by
contractual agreements (Guan and Zhao, 2010). Although the P-D planning is a popular
approach in the last two decades, to the best of our knowledge, it is revealed that there
has been little discussion about the P-D planning based on VMI so far. The sur vey
paper of the researches on the P-D models presented by Fahimnia et al. (2013) confirms
this gap. Therefore, to remove the mentioned potential challenges and to fill this gap,
this paper presents a novel approach that integrates the P-D planning and VMI for
manufacturing systems.
In this paper, a multi-objective non-linear optimization model for P-D planning is
presented based on the vendor-managed inventory (P-D-VMI) in a three-level supply chain
including several external suppliers at the first level, a single manufacturer at the second
level, and multiple retailers at the third level. The objectives are to minimize the total cost
of the manufacturer, the total cost of the retailers, and the total distribution time for the
products and the raw materials in the supply chain. In this paper, a Cobb-Douglas demand
function is considered where the demand faced by each retailer for each product is a
decreasing function of the retail price that is a decision variable. The aim of this function is
to establish a relationship between the retail price and the demand.
Since the proposed model is a non-convex non-linear programming, which is known
to be an NP-hard problem, the exact methods are not proper to be chosen as solving
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Production-
distribution
planning
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