 Open Access
 Total Downloads : 510
 Authors : Lokesh Malviya , Saurabh S Chandrawat, Dr Kapil Maheshwari
 Paper ID : IJERTV1IS8357
 Volume & Issue : Volume 01, Issue 08 (October 2012)
 Published (First Online): 29102012
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Application Of SC Concept For Designing The Effective Distribution Network For JVVNL
Lokesh Malviya , Saurabh S Chandrawat, Dr Kapil Maheshwari
Abstract
Distribution refers to the steps taken to move and store a product from the supplier stage to a customer stage in the supply chain. Distribution is a key driver of the overall profitability of a firm because it directly impacts both the supply chain cost and the customer experience. Good distribution can be used to achieve a variety of supply chain objectives ranging from low cost to high responsiveness. As a result, companies in the same industry often select very different distribution networks. The objective of this research is to study the existing distribution network of the JAIPUR VIDUT VITRAN NIGAM LIMITED (JVVNL), JAIPUR and develop a decision model using SOLVER IN EXCEL to assist restructuring of their distribution network. The model will decide the optimum number of distribution centres, their locations and supply matrix. The decision model will provide the solution by optimizing transportation cost and inventory costs.

Introduction
To serve customers in a cost effective way network design consists of decisions regarding the location of plants, suppliers and distribution centers the most important tactical issues that firms have to resolve include allocation of volumes to plants and allocation of plants to markets. The professionals verify their operations on a daily basis. The modern logistic leaders use the tricks like competitive pressures, mergers, acquisitions, new product lines and greater customer expectations, and so forth. This change is a cost of doing business in the latest
new economy. This research investigates the auction properties that influence efficiency (ability to maximize price and profit) as the distribution link of the supply chain. Also focuses on different key areas that are the roadmap to an effective, flexible and proactively responsive distribution operation (Chopra, 2001). Supply chain network
design involves strategic decisions on the number, locations, capacity and mission of the supply, production and facilities of a supply chain in order to provide goods to a predetermined, but possibly evolving, customer base (Kalvi and Martel,2009) Distribution refers to the steps taken to move and store a product from the supplier stage to a customer stage in the supply chain. Distribution is a key driver of the overall profitability of a firm because it directly impacts both the supply chain cost and the customer experience. Good distribution can be used to achieve a variety of supply chain objectives ranging from low cost to high responsiveness. As a result, companies in the same industry often select very different distribution networks.

Model Description and Result Analysis for a Distribution System
The objective of the research is to develop a distribution network under supply chain of the Jaipur Vidut Vitran Nigam Limited, Jaipur. The main objectives of the research could be stated in short as:

Analyze the existing distribution network.

Propose a new distribution strategy

Find the optimum number of distribution centers, their locations and

Decide the associate minimum cost.

Each model represents a specific business case; hence an optimization model with the suitable constraints was developed. Total cost concept is used along with mathematical optimization technique. The important components of cost used in developing this model are:

Fixed initial set up cost.

Transportation cost.

Inventory cost
After analyzing the current distribution strategy, a new strategy is proposed to overcome its
disadvantages. The highlights of the proposed distribution strategy are:

Each distribution center would store all products.

Each distribution center would serve only the customers in its proximity (no specific distance constraint was modeled).

Each customer would be served by only one distribution center.
The important steps in the development of the model can be described as,

Data collection.

Mathematical formulation.

Running the model.

Data Collection
While developing the model, following data is important:

Demand outline of the product.

Information regarding location of all customers, existing distribution centers.

Distance matrix (i.e. distance between any two locations)

Information regarding transportation cost, inventory cost etc.

The actual data for the fiscal year of 20092010 is used as input while building the model. The total product line of the company has around 98 active products. This resulted in hundreds of thousands of variables demanding high amount of software as well as hardware resources.

Data Collection of Demand Pattern of the Product:
The required data for the fiscal year of 2009 2010 is collected while designing the effective distribution network of JVVNL, RURAL JAIPUR. All required data are given below in the Table while building the model.

Statement showing 5 KVA single phase transformers issued to sub division:
Table 2.1: Data tabulation of 5KVA single phase transformer

Statement showing 16 KVA single phase transformers issued to subdivision:
Table 2.2: Data tabulation of 16KVA single phase transformers


Information Regarding Location of all Customers, Existing Distribution Centers
Statement showing position of sources in gps and (x,y) coordinates
Table 2.3: Data tabulation of position of sources in gps and (x,y) coordinates

Statement showing distance matrix from source to sub divisions:

Solvers, or optimizers, are software tools that help users find the best way to allocate scarce resources. The resources may be raw materials, machine time or people time, money, or anything else in limited supply. The "best" or optimal solution may mean maximizing profits, minimizing costs, or achieving the best possible quality.

Distribution and Networks Using Solver in Excel

Routing (of goods, natural gas, electricity, digital data, etc.) involves allocating something to different paths through which it can move to various destinations, to minimize costs or maximize throughput.

Loading (of trucks, rail cars, etc.) involves allocating space in vehicles to items of different sizes so as to minimize wasted or unused space.

Scheduling of everything from workers to vehicles and meeting rooms involves allocating capacity to various tasks in order to meet demand while minimizing overall costs
To use a solver, we must build a model that specifies:

The resources to be used, using
decision variables,

The limits on resource usage, called constraints, and

The measure to optimize, called the objective


Table 2.4: Data tabulation distance matrix from source to sub divisions

Mathematical Formulation
Once the new distribution strategy is identified, it is then translated into the mathematical form and a decision tool solver in excel. Formulation of a model using solver needs the model to be structured in followin few steps.

Preparing data base in an excel spreadsheet.

To use appropriate tool like solver

To get optimal results by using solver in excel.


Solver
In this paper, Gravity location model is being used as this described above in details and it is useful to identify suitable geographic locations within a region. The main purposes of Gravity models are to find locations that minimize the cost of transportation within supply chain.
Jaipur vidut vitran nigam Ltd has one store located near Sodala, Jaipur from which it has supplied the complete rural Jaipur district but there are few problems occurred in distribution of the products so it needs to set up other facility locations. Gravity models assume that both the sources and the markets can be located as grid points on a plane. All distances are calculated as the geometric distance between two points on the plane. This model also assumes that the transportation cost grows linearly with the quantity shipped. The basic inputs of the model as follows:

xn, yn – coordinate location of either markets or supply sources n

Fn – cost of shipping one unit for one km between the facility and either market or supply source n

Dn – quantity to be shipped between facility and market or supply source n

If (x,y) is the location selected for the facility, the distance dn between the facility at location (x,y) and the supply source or market n is given by
dn={(xxn)2 + (yyn)2} (1) The total transportation cost is given by
northern hemisphere). Eastings and northings are measured in meters. The point of origin of each UTM zone is the intersection of the equator and the zone's central meridian. In order to avoid dealing with negative numbers, the central meridian of each zone is given a "false easting" value of 500,000 meters. Thus, anything west of the central meridian will have an easting less than 500,000 meters. For example, UTM eastings range from 167,000 meters to 833,000 meters at the equator (these ranges narrow towards the poles). In the northern hemisphere, positions are measured northward from the equator, which has an initial "northing"
TC= Dn Fn dn
(2)
value of 0 meters and a maximum "northing" value of approximately 9,328,000 meters at the 84th
The optimal location is one that minimizes the TC in equation 2. The optimal solution is obtained using the solver tool in excel. The first step begins by arranging the data in an Excel spreadsheet. it uses six columns, first one for sources/markets, second one for transportations cost/ton km, third one for quantity in tons, fourth and fifth for x and y coordinates and last one for distance(d) and enter the formula for the model by referencing to the cells containing the model parameters. Next, set the two decision variables (X,

and a target cell which has objective function and then calculated using equation (2).
Here (x,y) is the location selected for the facility and are taken as geographical positioning system. The sources and the markets can be located as grid points on a plane and the distance dn between the facility at location (x,y) and the supply source or market n is calculated by above formula. The values of (x,y) are obtained as gps values for all sources and markets and then convert these values to (x,y) coordinates. These values are described by the Universal Transverse Mercator (UTM). The Universal Transverse Mercator (UTM) geographic coordinate system is a gridbased method of specifying locations on the surface of the Earth that is a practical application of a 2 dimensional Cartesian coordinate system. It is a horizontal position representation to identify locations on the earth independently of vertical position, but differs from the traditional method of latitude and longitude in several respects. The UTM system is not a single map projection. The system instead employs a series of sixty zones, each of which is based on a specifically defined secant transverse Mercator projection. (Military map reading, 2005)
A position on the Earth is referenced in the UTM system by the UTM zone, and the easting and northing coordinate pair. The easting is the projected distance of the position eastward from the central meridian, while the northing is the projected distance of the point north from the equator (in the
parallel the maximum northern extent of the UTM zones. In the southern hemisphere, northings decrease as you go southward from the equator, which is given a "false northing" of 10,000,000 meters so that no point within the zone has a negative northing value. As an example, the CN Tower is located at the geographic position 43Â°3833.24N 79Â°2313.7W/ 43.6425667Â°N
79.387139Â°W. This is in zone 17, and the grid position is 630084m east, 4833438m north. There are two points on the earth with these coordinates, one in the northern hemisphere and one in the southern. (Military map reading, 2005)
The next step is to use the tools/solver to invoke Solver. Within the solver parameters dialog box the following information is entered to represent the problem.

Set Target Cell

Equal to Select Min.

By changing Variables Cells

Subject to constraint
This is an existing distribution network of the JVVNL, Jaipur.
SE
Figure 2.1: Existing Distribution Network of JVVNL Storage with Direct Shipping

There are certain problems in such type of distribution network like higher transportation costs, longer response time, expensive and difficult to implement in case of return ability etc.


Modified Distribution Network
A survey is done to find the optimum number of distribution centers within the region. All sub division is situated on the four ways. First one on the delhi way, second one on the chomu way, third one on the ajmer way and last one jpdc only. These all are suitable locations to serve customer request. This means that there are four numbers of suitable locations in fulfilling customer demands.
The centerofgravity model helps determine the optimal location for an individual warehouse if proximity to customers is the only criterion. To select a site for an individual distribution center to serve local customers, the model suggests finding the location closest to the center of demand for all customers. Customers are assumed to be located on a grid system, each with a given fixed annual demand. The location of each customer is represented by x and y coordinates.
The following formula is used to find the COG location (x, y) for the warehouse.
X (1)
Y (2)
Where xi and yi are the coordinates of the ith customer, and di is annual demand of the ith customer.

Transportation Cost and Optimal Location
The optimal locations and Transportation Cost in the supply chain as a distribution centre or store is obtained by using Solver Tool. Again repeat the whole procedure as used in existing distribution network to obtain modify distribution. This time, there is a source (Poata) and four markets.
Figure 2.2: Model formulation containing solver parameters (source: Poata)

Click on the solver button and the optimal solution is returned in cells and thus identifies the coordinates (X,Y) = (3013631,407004) as the location of the new facility that minimizes the total cost as shown in Figure below:
Figure 2.2: Model formulation containing solver results (source: Poata)
From the map, these coordinates are close to the Poata sub division. The optimal location is Poata that minimizes the total transportation cost.
This time, there is a source (Jobner) and four markets.
Figure 2.4: Model formulation containing solver parameters (source: Jobner)

Click on the solver button and the optimal soltion is returned in cells and thus identifies the coordinates (X,Y) = (2983102,461813) as the location of the new facility that minimizes the total cost as shown in Figure below:
Figure 2.5: Model formulation containing solver results (source: Jobner)
From the map, these coordinates are close to the Jobner sub division. The optimal location is Jobner that minimizes the total transportation cost.
This time, there is a source (a1 Chomu) and four markets.
Figure 2.6: Model formulation containing solver parameters (source: a1 Chomu)

Click on the solver button and the optimal solution is returned in cells and thus identifies the coordinates (X,Y) = (3004323,428817) as the location of the new facility that minimizes the total cost as shown in Figure below:
This time, there is a source (JPDC) and four markets.
Figure 2.8: Model formulation containing solver parameters (source: modified JPDC)

Click on the solver button and the optimal solution is returned in cells and thus identifies the coordinates (X,Y) = (2975785,423808) as the location of the new facility that minimizes the total cost as shown in Figure below:
Figure 2.9: Model formulation containing solver results (source: JPDC modified)
From the map, these coordinates are close to the JPDC division. The optimal location is JPDC that minimizes the total transportation cost.
SE
Store (DCs)
Figure 2.7: Model formulation containing solver results (source: a1 Chomu)
From the map, these coordinates are close to the a1 Chomu sub division. The optimal location is a1 Chomu that minimizes the total transportation cost.
Figure 2.10: Modified Distribution Network of JVVNL Storage
The model developed in this research is run and results are obtained using few steps. In first step,
the model is made to choose the locations of the distribution centers by specifying the number of distribution centers desired in the network. The model is run for five times, first one for existing distribution and rest of modified distribution network in the supply chain.
Now, the total cost is obtained for each division. The total cost consist three costs mainly. These are listed below:

Fixed initial set up cost.

Transportation cost.

Inventory cost
The Total Transportation cost is obtained already by using solver tool and in next steps, inventory cost will be calculated


Assumption
Fixed initial set up cost is not being calculated because the optimal locations which obtained from solver very near to one of the sub divisions so there is no need to any infrastructure cost and machinery cost. Here two costs are being considered only.


Inventory cost

There are mainly three types of inventory cost:

Cycle inventory

Safety inventory

Intransit inventory
Cycle inventory (CI) = [lot size (Q)/2] (3) Safety inventory (SI) = [RLT/2days of demand] (4)
In transit inventory
(TI) = [total demand* (LT/365)] (5)
Some data are directly provided by the company only like holding cost in percentage, cost of item, total demand etc. those played an important role to obtain the total annual holding cost.
Table 2.5: Showing different values associate with inventory
In the above Table, Different values are calculated by using above equations and formulas and make an excel spreadsheet like CI, SI, TI and total annual holding cost of the different sources.
Total Annual Holding Cost (TAHC) of existing distribution network = 61912.3 Rs
Total Annual Holding Cost (TAHC) of modified distribution network
= 19978.1+ 9098.08 + 11970.7 + 18885.5
= 59932.3 Rs
Difference of Total Annual Holding Cost in both cases = 61912.3 59932.3 = 1980 Rs
This difference of Total annual holding cost in both cases can be ignored so total transportation cost will be considered as total cost. In both cases, total transportation cost has been obtained.
Total transportation cost of existing distribution network = 2492313 Rs
Total transportation cost of modified distribution network = 518669 + 218717 + 121143 + 481702
= 1340231 Rs
Difference of Total transportation cost in both cases = 2492313 1340231 = 1152082 Rs

Result
From the above calculations, it can be clearly seen that the total cost of the existing distribution network is less than the total cost of the modified distribution network. Hence it can be concluded that the optimum number of distribution centers the company should have is four. The locations are selected by the model as given below in the Table:
Table 3.1: Showing results
Calculate the efficiency of the distribution network
The efficiency of the distribution network = [(initial total cost final total cost)/(initial total cost)] = [(2492313 1340231)/ 2492313]* 1
= 46.22%
The model with four distribution centers results in approximate 46.22% of the cost savings. The proposed distribution network, suggests three distribution centers in the network than the present situation.

Conclusion
This research studied the problem of designing a distribution network under a supply chain system that involves determining the best locations stores and the best strategy for distributing the product from the plants to the stores and from the stores to the customers. This research is developed a model by using a tool Solver in Excel for the problem. The results of model indicate that the procedure is both effective and efficient for a wide variety of problem sizes and structures.
The results of this model indicate that large cost savings can be achieved through systematic analysis of the logistics process of this company. The model with four distribution centers results in approximate 46.22% of the cost savings. Optimally designed distribution network would primarily results in

Lower transportation costs

Increased customer service level

Decrease in order fulfillment lead time

Greater demand visibility as each distribution center will be closer to customers

This approach suggested here can be easily used to design any model under supply chain and can be flexibly updated to reflect any changes in the process, strategy or demand pattern. The well defined structure of the data sets allows easy maintenance of the data. Using solver tool in Excel requires relatively less time to compute the feasible solution. This is an important feature from the user point of view, since the user can build different scenarios by making necessary changes in the model and achieve the results relatively quickly so that all customer demand is satisfied at minimum total costs of the distribution network resulted from the Store location, transportation, and inventory. This model is developed for Jaipur Vidut Vitran Nigam Limited, Jaipur and minimized the expected total cost for designing an effective distribution network system in a supply chain.
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