INVESTIGATION the same time reduce transportation costs.

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industries face an enduring need for expansion and development in order to
sustain and grow in the market. There are numerous strategies that an industry
can use for expansion which are contingent upon its financial condition, its
competition and position in the market. Market expansion, market penetration,
product expansion, diversification and acquisition are some common growth
strategies. There are two reasons for a company to consider market expansion,
new users for the product in other markets or no room for growth in the current
market. In this project, we are associated with a small – scale wet grinder
manufacturing industry, JRS Engineering. The industry plans to set up a new
facility, both for manufacturing and warehousing in order to penetrate into a
market and at the same time reduce transportation costs. The various factors
that affect location decisions are location of raw material or supplies,
location of markets, labour, taxes, environmental regulations, land,
development support, etc., The industry has proposed two major locations in the
city with growing market for wet grinders, for which investigation has to be
done to determine the optimal location. There are various techniques for
determining the optimal location, namely Factor Rating method, Load Distance
method, Centre of Gravity method, Break- Even analysis, etc., Based on these
methods, using market population as the load, a detailed analysis is to be
carried out to determine the optimal location from the two proposals, which
will be utilised to set up the new facility. Also, setting up of the new
facility has an impact on the inventory levels that have to be maintained at
the two facilities. This creates a need to determine the optimum size of
warehouse required to avoid excess inventory or stock-out.









Logistics and the supply chain involve many complex
activities, which require optimal strategic decisions in order to operate
efficiently and effectively. Logistics managers are under a great amount of
stress as the industry is ever changing. Management needs to adjust and improve
all activities being conducted. Facility location is a crucial element in the
supply chain and has a great impact on the efficiency of numerous logistics
activities. Facility locations involve numerous aspects, such as the location
of manufacturing plants, assembly locations as well as distribution centres.
The location of the facility plays an important role in the success of
logistics networks.

The importance of facility location is gaining much
attention in today’s day and age as companies are rapidly realizing the
importance and advantages of a successful facility location as well as the
disadvantages involved in the selection of an unsuccessful facility location.
The main focus of logistics is to reduce costs, improve efficiency as well as
customer service. Successful facility location decisions may lead to drastic
cost reductions as well as an improvement in the customer service levels. An
unsuccessful facility location decision may lead to inefficient operations and
additional costs, which drastically affects the competency and effectiveness of
the overall operation. Logistics managers are critically evaluating the
performance of current facility locations.

Changing conditions in technology and growing competition in the business
environment have forced organizations to invest in and focus on their logistics
systems. Strategic decisions regarding the location of facilities such as
plants, distribution centres and retailers have a strong impact on the
profitability of supply chains. The first step in
creating any supply chain is the geographic placement of production facilities,
sourcing points, and stocking points. The location of facilities involves a
commitment of resources to a long-term plan. The possible path by which the product
flows through to the final customer is determined after the size, number, and
location of facilities are determined. These decisions are of great
significance to a firm since they represent the basic strategy for accessing
customer markets, and will have a considerable impact on revenue, cost, and
level of service

Well-planned location decisions enable efficient flow of materials
through the distribution system, and lead to decreased costs and improved
customer service.






Ø  Estimation of product or service demand in the system

Ø  To identify the factors that influences the facility location decision

Ø  To formulate the facility location problem 

Ø  To develop location alternatives

Ø  To evaluate location alternatives

Ø  To minimize
total costs:

external supply


inventory holding costs

fixed facility operating costs



















Gama et al., (2009) reviewed facility location models in the context of supply
chain management and identified
basic features that such models must capture to support decision-making
involved in strategic supply chain planning. In particular, the integration of
location decisions with other decisions relevant to the design of a supply
chain network has been discussed. Furthermore, aspects related to the structure
of the supply chain network, including those specific to reverse logisticshas
been addressed. Significant contributions to the current state-of-the-art have
been surveyed taking into account numerous factors. Also, supply chain
performance measures and optimization techniques have been reviewed. Finally, a
list of issues requiring further research has been highlighted.

Farahani and Arabani, (2012) have investigated
the dynamics of facility location
problems (FLPs) ought to be taken into account so as to efficiently deal with
changing parameters such as market demand, internal and external factors, and
populations. They have reported on
literature pointing out some aspects and characteristics of the dynamics of
FLPs. They have not only reviewed most variants of these problems, but have also
to provided a broad overview of their mathematical formulations. Finally, based
on classified research works and available gaps in the literature, some
possible research trends have been pointed out.

Park et al., (2017) have investigated how firms make plant location and
inventory level decisions to serve global markets. In their analysis, they have
considered not only differences in wages, transportation costs, and subsidies
across countries but also exchange rate changes and competition between firms.
They have presented that the degree of risk exposure of firms and the benefit
of relocating plants to the final consumption market played a critical role in
firms’ plant location decisions, especially when the global economy is highly
uncertain. Furthermore, they have provided the conditions under which a firm
relocates its plant from one country to another, and empirically validates the
results. Also, they have investigated how a firm manages inventory when its
plant is located in a foreign country. Finally, they have confirmed the
predictions of the theory empirically by using a unique firm-level dataset
drawn from Korean firms.


Diabat et al., (2017) have presented a joint location-inventory model for the
network design of a supply chain with multiple Distribution Centers (DCs) and
retailers. The developed model determined the number and location of DCs, the
assignment of retailers to DCs, and the size and timing of orders for each DC.
The uncertain natures of demands and replenishment lead times have been
incorporated into the model utilizing a queuing approach. To solve the
presented model for large size problems, a hybrid solution algorithm based on
simulated annealing and direct search method has been adopted. The comparative
analysis of the numerical results provided important modeling insights.
Particularly, they have demonstrated numerically that the cost savings obtained
from the queuing approach could be significant.

Nagurney (2010) has proposed a framework for supply chain network design
and redesign that allows for the determination of the optimal levels of
capacity and operational product flows in the supply chain. Both the design and
redesign problems have been formulated as variational inequalities. The same
algorithm, which exploits the underlying network structure, can be used for the
solution of either problem. Moreover, the new framework with numerical examples
has been illustrated, that demonstrated the practicality and flexibility of the

Meng et al., (2009) have addressed a novel competitive facility location
problem about a firm that intends to enter an existing decentralized supply
chain comprised of three tiers of players with competition: manufacturers,
retailers and consumers. Firstly, they have proposed a variational inequality
for the supply chain network equilibrium model with production capacity
constraints, and then employed the logarithmic-quadratic proximal
prediction–correction method as a solution algorithm. Based on this model, generic
mathematical program has been developed with equilibrium constraints for the
competitive facility location problem, which can simultaneously determine
facility locations of the entering firm and the production levels of these
facilities so as to optimize an objective. Subsequently, a hybrid genetic
algorithm that incorporates with the logarithmic-quadratic proximal prediction–correction
method has been developed for solving the proposed mathematical program with an
equilibrium constraint. Finally, some numerical examples have been carried out to
evaluate proposed models and solution algorithms.

Farahani et al., (2012) have
reviewed the covering problems in facility
location. Here, besides a number of reviews on covering problems, a
comprehensive review of models, solutions and applications related to the
covering problem have been presented. The covering problems have been outlined
and then the solutions have been investigated.



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